CHARACTERIZATION AND IDENTIFICATION OF HUMAN MESENCHYMAL STEM CELLS AT MOLECULAR LEVEL

A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES

OF MIDDLE EAST TECHNICAL UNIVERSITY

BY

CEREN AKSOY

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR

THE DEGREE DOCTOR OF PHILOSOPHY IN

BIOTECHNOLOGY

MARCH 2012

Approval of the Thesis

CHARACTERIZATION AND IDENTIFICATION OF HUMAN MESENCHYMAL STEM CELLS AT MOLECULAR LEVEL

submitted by CEREN AKSOY in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biotechnology Department, Middle East Technical University by,

Prof. Dr. Canan Özgen Dean, Graduate School of Natural and Applied Sciences

Prof. Dr. Nesrin Hasırcı Head of Department, Biotechnology

Prof. Dr. Feride Severcan Supervisor, Biological Sciences Dept., METU

Examining Committee Members:

Prof. Dr. Ufuk Gündüz Biological Sciences Dept., METU Prof. Dr. Feride Severcan Biological Sciences Dept., METU Assoc. Prof. Dr. Ayşen Tezcaner Engineering Sciences Dept., METU Assoc. Prof. Dr. İhsan Gürsel Molecular Biology and Genetic Dept., Bilkent Univ. Assoc. Prof. Dr. Ayşen Günel Özcan Faculty of Medicine, Hacettepe Univ.

Date:

iii

I hereby declare that all information in this document has been obtained and presented in accordance with academic rules and ethical conduct. I also declare that, as required by these rules and conduct, I have fully cited and referenced all material and results that are not original to this work.

Name, Last name: Ceren Aksoy

Signature :

iv

ABSTRACT

CHARACTERIZATION AND IDENTIFICATION OF HUMAN

MESENCHYMAL STEM CELLS AT MOLECULAR LEVEL

Aksoy, Ceren

PhD, Department of Biotechnology

Supervisor: Prof. Dr. Feride Severcan

Co-Supervisor: Prof. Dr. Duygu Uçkan Çetinkaya

March 2012, 154 pages

Bone marrow mesenchymal stem cells (BM-MSCs) are pluripotent cells that can

differentiate into a variety of non-hematopoietic tissues. They also maintain

healthy heamatopoiesis by providing supportive cellular microenvironment into

BM. In this thesis, MSCs were characterized in terms of their morphological,

immunophenotypical and differentiation properties. Then, they were examined by

attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy

together with hierarchical clustering, and FTIR microspectroscopy.

In the first part of this study, global structural and compositional changes in BM-

MSCs during beta thallasemia major (β-TM) were investigated. The significant

increase in lipid, protein, glycogen and nucleic acid concentrations in thalassemic

MSCs with respect to healthy MSCs were attributed to enhanced cell proliferation

and BM activity during ineffective erytropoiesis (IE). MTT assay results reflected

v

increase in cellular activity of thallasemic BM-MSCs. The significant decreases in

the concentrations of the mentioned macromolecules after BM transplantation

therapy were interpreted as recovery of IE. Based on these changes, sampling

groups were successfully discriminated by using cluster analysis.

In the second part of this study, it was aimed to identify new molecular marker(s)

in order to determine the effects of donor age on healthy BM-MSCs. The spectral

results reflected that there were significant increases in the concentrations of

saturated lipids, proteins, glycogen and nucleic acids in children and adolescent

group BM-MSCs when compared with the infants, early and mid adults. These

results were interpreted as increased proliferation activity in younger BM-MSCs.

The results of MTT assay clarified the increased cellular activity. Spectral data of

five different sampling groups was discriminated by hierarchical cluster analysis.

The FTIR microspectroscopic imaging study was also performed in two different

parts of the study in order to support the ATR-FTIR spectroscopy results. The

FTIR microspectroscopic results were found in agreement with ATR-FTIR

spectroscopy results.

Key words: Bone marrow mesenchymal stem cells, bone marrow transplantation,

beta thalassemia major, donor age effect, attenuated total reflection- Fourier

transform infrared (ATR-FTIR) spectroscopy, Fourier transform infrared (FTIR)

microspectroscopy.

vi

ÖZ

İNSAN MEZENKİMAL KÖK HÜCRELERİNİN MOLEKÜLER SEVİYEDE KARAKTERİZASYONU VE TANIMLANMASI

Aksoy, Ceren

Doktora, Biyoteknoloji Bölümü

Tez Yürütücüsü: Prof. Dr. Feride Severcan

Ortak Tez Yürütücüsü: Prof. Dr. Duygu Uçkan Çetinkaya

Mart 2012, 154 sayfa

Kemik iliği mezenkimal kök hücreleri (Kİ-MKH) hematopoetik olmayan, çok

sayıda farklı doku hücresine farklılaşabilme özelliği olan hücrelerdir. Bu hücreler

kemik iliği mikroçevresi için destek görevi görerek sağlıklı bir hematopoezin

devamını sağlarlar. Bu tez kapsamında, Kİ-MKH’leri morfolojik,

immunofenotipik ve farklılaşma özellikleri bakımından karakterize edilmişlerdir.

Daha sonra attenuated total reflectance-Fourier dönüşüm kızılötesi spektroskopisi

(ATR-FTIR), kümeleme analizi ve FTIR mikrospektroskopisi yöntemleri ile

incelenmişlerdir.

Çalışmanın ilk kısmında, Kİ-MKH’lerinde beta talasemi major hastalığı süresince

meydana gelen genel yapısal ve kompozisyonel değişimler araştırılmıştır.

Talasemik Kİ-MKH’lerinde sağlıklı Kİ-MKH’lerine göre lipit, protein, glikojen ve

nükleik asit konsantrasyonlarında görülen artışlar inefektif eritropoez (IE)

süresince artan hücresel aktivite ve Kİ aktivitesi olarak yorumlanmıştır.

vii

Bahsedilen bu makromoleküllerin konsantrasyonları Kİ nakli sonrasında anlamlı

olarak azalmıştır. MTT testi ile talasemik hücrelerdeki hücresel aktivite artışı

gösterilmiştir. Bu azalış Kİ nakli sonrasında IE’in iyileşmesi olarak

yorumlanmıştır. Bu değişimlere göre örneklem grupları kümeleme analizi ile

başarılı bir şekilde birbirlerinden ayrılmışlardır.

Çalışmanın ikinci kısmında donor yaşının sağlıklı Kİ-MKH’leri üzerine etkilerini

belirleyebilmek için yeni moleküler belirteçlerin bulunması amaçlanmıştır.

Spectral sonuçlar, çocuk ve adolesan çağındaki sağlıklı donörlerin Kİ-

MKH’lerinde doymuş lipit, protein, glikojen ve nükleik asitlerin

kontsantrasyonlarında bebek, erken yaş ve ileri yaş erişkinlerin Kİ-MKH’lerine

göre anlamlı artışlar olduğunu göstermiştir. Bu sonuçlar daha genç yaştaki

donörlerden alınan hücrelerde artmış hücresel aktivite olarak yorumlanmıştır ve bu

sonuç MTT testi ile doğrulanmıştır. Beş farklı yaş grubuna ait Kİ-MKH’lerin

spectral verileri kümeleme analizi ile ayrılmıştır.

FTIR mikrospektroskopik görüntüleme deneyleri ile çalışmanın her iki

bölümünden elde edilen ATR-FTIR spektroskopisi sonuçları desteklenmiştir.

FTIR mikrospekrospi deneylerinin sonuçları ATR-FTIR spektroskopisi ile aynı

yönde çıkmıştır.

Anahtar Kelimeler: Kemik iliği mezenkimal kök hücresi, kemik iliği nakli, beta

talasemi major, donör yaşı etkisi, attenuated total reflectance-Fourier dönüşüm

kızılötesi spektroskopisi (ATR-FTIR), Fourier dönüşüm kızılötesi spektroskopisi

(FTIR) mikrospektroskopi.

viii

To my parents Aliye and Mevlüt Aksoy,

ix

ACKNOWLEDGEMENTS

I would like to express my deepest gratitude to my supervisor Prof. Dr. Feride

Severcan for her valuable guidance, continued advice and encouragement

throughout this study.

I am also grateful to my co-supervisor Prof. Dr. Duygu Uçkan Çetinkaya for her

continuous help, suggestions and support in this study.

I would like to extend my thanks to the members of my thesis follow-up

committee Assoc. Prof. Dr. Ayşen Tezcaner and Assoc. Prof. Dr. İhsan Gürsel for

their constructive contributions during this study.

I wish to send my special thanks to Fatima Aerts Kaya, Sevil Arslan, Emine Kılıç,

and Özlem Küçükbayrak in PEDİSTEM Lab. Group for their friendship and their

endless support during experimental period.

My special thanks go to my labmates; Şebnem Garip, Özlem Bozkurt, Nihal

Şimşek Özek, Sevgi Türker, Seza Ergün, Damla Güldağ, İlke Şen and Ebru Aras.

Thank you for sharing all challenges and all good times for many years. I want to

express my special thanks to Nusrettin Güleç for his existence and main

motivation in the completion of this study.

I would like to give my deepest thanks to my mother Aliye Aksoy for her endless

love and numerous sacrifices in my life.

I am grateful to my brother Taylan Aksoy for his friendship and love during all my

life. He has always been my best friend and confidant. Thanks goodness for his

existence in my life.

x

TABLE OF CONTENTS

ABSTRACT ............................................................................................................iv

ÖZ............................................................................................................................vi

ACKNOWLEDGEMENTS.....................................................................................ix

TABLE OF CONTENTS..........................................................................................x

LIST OF TABLES.................................................................................................xvi

LIST OF FIGURES..............................................................................................xvii

LIST OF ABBREVIATIONS................................................................................xxi

CHAPTERS

1. INTRODUCTION..............................................................................................1

1.1 What is Stem Cell ?.....................................................................................1

1.2 Mesenchymal Stem Cells.............................................................................2

1.2.1. Characteristics of Mesenchymal Stem Cells.........................................3

1.2.1.1. Phenotype of Mesenchymal Stem Cells........................................4

1.2.1.2. Production of Cytokines and Growth Factors...............................5

1.2.1.3. Differentiation Capacity of Mesenchymal Stem Cells.................5

1.3 Clinical Usage of Mesenchymal Stem Cells...............................................7

1.4 Mesenchymal Stem Cells as a Main Cellular Component of the Bone

Marrow Microenvironment and Hematopoiesis..........................................7

1.5 What is Thalassemia ?.................................................................................8

1.5.1 Beta Thalassemia Major......................................................................10

1.5.2 Ineffective Erythropoiesis...................................................................10

1.5.3 Hematopoietic Stem Cell Transplantation Therapy in Beta

Thalassemia Major.............................................................................11

1.6 HSC and MSC Interactions in Bone Marrow Microenvironment: Stem

Cell Niche..................................................................................................12

xi

1.7 Aging of Stem Cell Niches and Intrinsic Aging of Mesenchymal Stem

Cells...........................................................................................................14

1.8 Optical Spectroscopy.................................................................................15

1.8.1 Basis of the Spectroscopy...................................................................15

1.8.2 Infrared Spectroscopy.........................................................................19

1.8.2.1 The Fourier Transform Infrared Spectroscopy (FTIR)………..21

1.8.2.1.1 Advantages of FTIR Spectroscopy………………………..22

1.8.2.1.2 Attenuted Total Reflectance Fourier Transform Infrared

(ATR-FTIR) Spectroscopy.................................................24

1.8.2.2 Fourier Transform Infrared Microspectroscopy.......................27

1.8.3 Infrared Spectroscopy in Stem Cell Researches.................................29

1.9 Aim of the Study........................................................................................31

2. MATERIALS AND METHODS .....................................................................34

2.1 Materials .....................................................................................................34

2.1.1 Chemicals............................................................................................34

2.1.2 Mesenchymal Stem Cells and Hematopoietic Stem Cells..................34

2.1.2.1 Sampling Groups.........................................................................34

2.1.2.1.1 Study 1..................................................................................34

2.1.2.1.2 Study 2..................................................................................35

2.2 Methods.......................................................................................................35

2.2.1 Cell Culture Experiments....................................................................35

2.2.1.1 Isolation and Cultivation of Mesenchymal Stem Cells from

Human Bone Marrow Samples.....................................................35

2.2.1.2 Freezing and Storage of Bone Marrow Mesenchymal Stem

Cells..............................................................................................36

2.2.1.3 Characterization of Bone Marrow Mesenchymal Stem Cells.......37

2.2.1.3.1 Morphological Assessment………………………………...37

2.2.1.3.2 Differentiation Experiments………………………………..37

2.2.1.3.2.1 Adipogenic Differentiation.............................................37

xii

2.2.1.3.2.1.1 Oil Red O Staining for Adipogenic Differentiation

Assessment..............................................................38

2.2.1.3.2.2 Osteogenic Differentiation.............................................38

2.2.1.3.2.2.1 Alizerin Red Staining for Osteogenic Differentiation

Assessment..............................................................39

2.2.1.3.3 Immunophenotyping of Bone Marrow Mesenchymal Stem

Cells by Flow Cytometry .....................................................39

2.2.1.3.3.1 Cell Surface Marker Staining............................................39

2.2.1.3.3.2 Flow Cytometry Analysis.................................................40

2.2.1.4 MTT (Thiazolyl Blue Tetrazolium Bromide) Proliferation

Assay.............................................................................................40

2.2.1.5 Determination of Erythropoietin (EPO) and Growth

Differentiation Factor 15 (GDF 15) Levels in Bone Marrow

Plasma Samples.............................................................................41

2.2.1.6 Analysis of Chimerism by Short Tandem Repeat Polymerase

Chain Reaction (STR-PCR) .........................................................42

2.2.2 Fourier Transform Infrared (FTIR) Spectroscopy and

Microspectroscopy Experiments.........................................................43

2.2.2.1 Attenuated Total Reflectance (ATR-FTIR) Spectroscopy

Study.............................................................................................43

2.2.2.1.1 Sample Preparation...............................................................43

2.2.2.1.2 Data Acquisition and Spectroscopic Measurements.............43

2.2.2.1.3 Statistical Analysis................................................................46

2.2.2.1.4 Cluster Analysis....................................................................46

2.2.2.2 FTIR Microspectroscopic Study...................................................47

2.2.2.2.1 Slide Preparation...................................................................47

2.2.2.2.1.1 Deposition and Fixatition of BM-MSCs on Low-e

Microscope Slides.........................................................47

2.2.2.2.2 Collection of Visible Images and Spectral Maps..................49

xiii

2.2.2.2.2.1 Selection of Spectral Images and Preprocessing of

Spectral Data.................................................................49

3. RESULTS ........................................................................................................51

3.1 Harvesting of Mesenchymal Stem Cells from Bone Marrow Samples by

Culturing....................................................................................................51

3.2 Characterization of Human Bone Marrow Mesenchymal Stem Cells.......54

3.2.1 Flow Cytometry Analysis of CD Marker Expression Profile of Bone

Marrow Mesenchymal Stem Cells.....................................................54

3.2.2 Differentiation Analysis of Bone Marrow Mesenchymal Stem

Cells....................................................................................................56

3.2.2.1 Adipogenic Differentiation Analysis..........................................56

3.2.2.2 Osteogenic Differentiation Analysis............................................58

3.3 Results of Chimerism Analysis Following Bone Marrow

Transplantation..........................................................................................60

3.4 FTIR Spectroscopy Results……………………………………………...61

3.4.1 General FTIR Spectrum and Band Assignments of Thalassemic and

Healthy Control Bone Marrow Mesenchymal Stem Cells.................62

3.4.2 Comparison of Spectra of Thalassemic and Healthy Control Bone

Marrow Mesenchymal Stem Cells.....................................................65

3.4.2.1 General Information about Numerical Comparisons of the Bands

of Thalassemic and Healthy Control Bone Marrow Mesenchymal

Stem Cells.....................................................................................68

3.4.2.2 Detailed Spectral Analysis of Thalassemic and Healthy Control

Bone Marrow Mesenchymal Stem Cells......................................69

3.4.2.2.1 Comparison of Thalassemic and Healthy Control Bone

Marrow Mesenchymal Stem Cells in the 3050-2800 cm-1

region......................................................................................69

xiv

3.4.2.2.2 Comparison of Thalassemic and Healthy Control Bone

Marrow Mesenchymal Stem Cells in the 1800-800 cm-1

region....................................................................................72

3.4.2.3 Cluster Analysis…………………………………………………75

3.4.2.4 FTIR Microspectroscopic Analysis and Comparison of

Thalassemic and Healthy Control Bone Marrow Mesenchymal

Stem Cells...……………………………………………………..80

3.4.3 Comparison of Spectra of Bone Marrow Mesenchymal Stem Cells

from Different Age Groups…...…………………………………….85

3.4.3.1 General Information about Numerical Comparisons of the Bands

of Bone Marrow Mesenchymal Stem Cells from Different Age

Groups…………………………………………………………...85

3.4.3.2 Detailed Spectral Analysis of Bone Marrow Mesenchymal Stem

Cells from Different Age Groups……………………...………...85

3.4.3.2.1 Comparison of Bone Marrpw Mesenchymal Stem Cells from

Different Age Groups in the 3050-2800 cm-1

region....................................................................................86

3.4.3.2.2 Comparison of Bone Marrow Mesenchymal Stem Cells from

Different Age Groups in the 1800-800 cm-1 region..............92

3.4.3.3 Cluster Analysis............................................................................97

3.4.3.4 FTIR Microspectroscopic Analysis and Comparison of Bone

Marrow Mesenchymal Stem Cellsfrom Different Age

Groups.........................................................................................101

3.5 MTT (Thiazolyl Blue Tetrazolium Bromide) Proliferation Assay...........104

3.6 Erythropoietin (EPO) and Growth Differentiation Factor 15 (GDF 15)

Levels in Bone Marrow Plasma Samples................................................107

4. DISCUSSION ................................................................................................108

4.1 The Effects of Beta Thalassemia Major on Bone Marrow Mesenchymal

Stem Cells................................................................................................108

xv

4.2 The Effects of Donor Age on Healthy Bone Marrow Mesenchymal Stem

Cells.........................................................................................................119

5. CONCLUSION...............................................................................................127

REFERENCES................................................................................................130

APPENDICES

A. CHEMICALS............................................................................................150

CURRICULIUM VITAE................................................................................151

xvi

LIST OF TABLES

TABLES

Table 2.1 The integrated spectral regions...............................................................50

Table 3.1 General band assignment of human bone marrow mesenchymal stem

cells.........................................................................................................................64

Table 3.2 Changes in the wavenumber and area vallues of some infrared bands for

the healthy control, pre- and post-transplant BM-MSCs........................................70

Table 3.3 Changes in the band area values of the infrared bands for control, pre

and post transplant BM-MSCs................................................................................71

Table 3.4 Numerical summary of the detailed differences in the lipid-to-protein

ratios of control and thalassemic BM-MSCs spectra..............................................75

Table 3.5 The band area values of healthy BM-MSCs from five different age

groups......................................................................................................................88

Table 3.6 MTT proliferation assay results of thalassemic and healthy control BM-

MSCs.....................................................................................................................106

Table 3.7 MTT proliferation assay results of P3 BM-MSCs obtained from healthy

donors of different age groups..............................................................................106

xvii

LIST OF FIGURES

FIGURES

Figure 1.1 Mesenchymal stem cells..........................................................................3

Figure 1.2 The mesengenic process..........................................................................6

Figure 1.3 The structure of hemoglobin....................................................................9

Figure 1.4 Electromagnetic wave............................................................................16

Figure 1.5 Energy level diagram illustrating the ground and first excited electronic

energy level.............................................................................................................17

Figure 1.6 The Electromagnetic Spectrum.............................................................19

Figure 1.7 The schematic representation of some molecular vibrations.................20

Figure 1.8 Schematic represantation of a Michelson Interferometer......................22

Figure 1.9 ZnSe Diamond ATR attachment of Perkin Elmer Spectrum 100 FTIR

Spectrmeter.............................................................................................................25

Figure 1.10 Schematic representation of ATR top plate………………………….26

Figure 1.11 Perkin Elmer Spectrum Spotlight 400 imaging FTIR microscope......28

Figure 2.1 Infrared spectrum of air.........................................................................44

Figure 2.2 The ATR FTIR spectrum of PBS buffer solution..................................45

Figure 2.3 Inverted ligth microscopy images of MSCs were directly grown on

silver coated low-e FTIR microscopy slides...........................................................48

Figure 3.1 Photomicrograph of BM-MNCs in culture flask during their expansion

phases to obtain P0 MSCs.......................................................................................52

Figure 3.2 Healthy BM-MSCs at different passages..............................................53

Figure 3.3 The FSC/SSC parameters of passage 3 BM-MSCs...............................55

Figure 3.4 Surface antigen profile of healthy BM-MSCs at passage 3 ..................55

Figure 3.5 Surface antigen profile of thalassemic BM-MSCs at passage 3............56

xviii

Figure 3.6 Oil Red O staining of thalassemic and healthy control BM-MSCs at the

end of 21 days.........................................................................................................57

Figure 3.7 Oil Red O staining of healthy P3 BM-MSCs from five different age

groups at the end of 21 days...................................................................................58

Figure 3.8 Alizerin Red staining of thalassemic and healthy control BM-MSCs at

the end of 21 days...................................................................................................59

Figure 3.9 Alizarin Red staining of healthy P3 BM-MSCs at the end of 21 days..60

Figure 3.10 The representative average spectra of healthy control, pre-transplant

and post-transplant group human bone marrow mesenchymal stem cells in the

3800-800 cm-1 region..............................................................................................63

Figure 3.11 The representative infrared spectra of healthy control, pre-transplant

and post-transplant group human bone marrow mesenchymal stem cells in the

3050-2800 cm-1 region............................................................................................66

Figure 3.12 The represantative infrared spectra of healthy control, pre-transplant

and post-transplant group human bone marrow mesenchymal stem cells in the

1800-800 cm-1 region..............................................................................................67

Figure 3.13 Hierarchical cluster analysis of healthy control, pre- and post-

transplant group MSCs in the 3050-800 cm-1 spectral region................................77

Figure 3.14 Hierarchical cluster analysis of healthy control, pre- and post-

transplant group MSCs in the 3050-2800 cm-1 spectral region..............................78

Figure 3.15 Hierarchical cluster analysis of healthy control, pre and post-transplant

group MSCs in the 1800-800 cm-1 spectral region.................................................79

Figure 3.16 Spectral image maps of healthy control, pre- and post-transplant

MSCs, which were derived from the peak integrated areas of CH2 antisymmetric

stretching band........................................................................................................81

Figure 3.17 Spectral image maps of healthy control, pre and post transplant MSCs,

which were derived from the peak integrated areas of CH2 symmetric stretching

band.........................................................................................................................82

xix

Figure 3.18 Spectral image maps of healthy control, pre and post transplant BM-

MSCs. A) Chemical maps were derived from the peak integrated areas of amide I

and B) chemical maps were derived from the peak integrated areas of amide II

band.........................................................................................................................83

Figure 3.19 Spectral image maps of healthy control, pre and post transplant MSCs,

which were derived from the peak integrated areas of PO2- antisymmetric

stretching band........................................................................................................84

Figure 3.20 The represantative infrared spectra of healthy BM-MSCs from five

different age groups in the 3800-800 cm-1 region...................................................87

Figure 3.21 The representative infrared spectra of healthy BM-MSCs from five

different age groups in the 3000-2800 cm-1 region.................................................89

Figure 3.22 The represantative infrared spectra of of healthy BM-MSCs from five

different age groups in the 1800-800 cm-1 region...................................................93

Figure 3.23 Hierarchical cluster analysis performed on the first-derivative and

vector normalized spectra of BM-MSCs of infants, children, adolescents, early and

mid adults in the 3000-800 cm-1 spectral region.....................................................98

Figure 3.24 Hierarchical cluster analysis performed on the first-derivative and

vector normalized spectra of BM-MSCs of infants, children, adolescents, early and

mid adults in the 3000-2800 cm-1 spectral region...................................................99

Figure 3.25 Hierarchical cluster analysis performed on the first-derivative and

vector normalized spectra of BM-MSCs of infants, children, adolescents, early and

mid adults in the 1800-800 cm-1 spectral region...................................................100

Figure 3.26 Spectral image maps of BM-MSCs from five different age groups,

which were derived from the peak integrated areas of CH2 antisymmetric

stretching band......................................................................................................101

Figure 3.27 Spectral image maps of BM-MSCs from five different age groups,

which were derived from the peak integrated areas of CH2 symmetric stretching

band.......................................................................................................................102

xx

Figure 3.28 Spectral image maps of from five different age groups MSCs, which

were derived from the peak integrated areas of amide I band..............................103

Figure 3.29 Spectral image maps of from five different age groups BM-MSCs,

which were derived from the peak integrated areas of amide II...........................103

Figure 3.30 Spectral image maps of from five different age groups BM-MSCs,

which were derived from the peak integrated areas of PO2- antisymmetric

stretching band......................................................................................................104

xxi

LIST OF ABBREVIATIONS

ATR-FTIR Attenuted Total Reflectance Fourier Transform Infrared

BaF2 Barium Floride

BM Bone Marrow

BMT Bone Marrow Transplantation

BM-MSC Bone Marrow Mesenchymal Stem Cell

β-TM Beta Thalassemia Major

CaF2 Calcium Floride

CD Cluster of differentiation

CO2 Carbondioxide

DMEM-LG Dulbecco's modified Eagle's medium – low glucose

DMSO Dimethyl sulfoxide

DNA Deoxyribonucleic Acid

dH2O Distilled Water

EDTA Ethylenediaminetetraacetic acid

EPO Erythropoietin

ELISA Enzyme Linked-Immunosorbent Assay

ES Embryonic stem

FACS Fluorescene-activated cell sorting

FBS Fetal Bovine Serum

FITC Fluorescein isothiocyanate

FTIR Fourier Transform Infrared

GDF15 Growth Differentiation Factor 15

HSC Hematopoietic Stem Cell

HCL Hydrocholoric Acid

HSCT Hemopoietic Stem Cell Transplantation

xxii

IE Ineffective Erythropoiesis

IR Infrared

MNC Mononuclear Cell

MSC Mesenchymal stem cell

N2 Nitrogen

PBS Phosphate buffered saline

PCR Polymerase Chain Reaction

RT Room Temperature

SC Stem Cell

SDS Sodium Dodesyl Sulphate

STR-PCR Short Tandem Repeat-Polymerase Chain Reaction

ZnSe Zinc Selenide

1

CHAPTER 1

INTRODUCTION

1.1. What is Stem Cell?

Stem cells are unique cells with ability to self-renew for a long time and to give

rise to different cell types that make up the tissues and organs of the body. The

ability to differentiate into different cell types is called as plasticity. Stem cells

may be isolated from embryo, umbilical cord and several adult tissues, and

differentiation potention of them varies depending on where they originate from

(Kelly, 2007; Panno, 2005).

Embryonic stem (ES) cell is obtained from the inner cell mass of the early (4 to 5

days) embryo called as blastocyst (Figure 1.1) (Chung et al., 2008). ES cells are

capable of unlimited number of symmetrical divisions without differention, which

means they have long-term self-renewal ability (Kirschstein, 2001). When they are

cultured in appropriate media and culture conditions, they can be induced to

differentiate selectively into more specialized populations. ES cells are pluripotent

and they can differentiate into every cell types in the body. Therefore, they are

very attrative candidates for wide range of tissue regeneration and cellular

therapies in regenerative medicine (Ami et al., 2008). To date, there has been

some success in inducing mouse ES cells to form particular types of cells, such as

cardiomyocytes, smooth muscle cells, neuron cells, and hepatocytes (Thumanu et

al., 2011).

2

Adult stem cells are multipotent cells found in a differentiated tissues and organs.

They can renew themselves for a long periods of time by making identical copies

and they can differentiate into all of the specialized cell types of the tissues from

which they originate (Kirschstein, 2001). They exist in various tissues such as

blood, bone marrow, cord blood, kidney, adipose tissue, teeth. Adult stem cells are

important for homeostatis by keeping the number of stem cells constant and for

self renewal of tissues during cellular aging and diseases (Orlic et al., 1999;

Perkins, 1998). Adult stem cells can arise from any organ or tissue including

hematopoietic or mesenchymal tissues; thus called as hematopoietic stem cells

(HSCs) or mesenchymal stem cell (MSC), respectively. HSCs, are obtained from

bone marrow, periferal blood, umbical blood, generate all types of blood cells by

the process called as hematopoiesis. Another population of adult stem cells is

called as mesenchymal stem cells, which can be isolated from many types of

tissues and also can be differentiated into mesenchym originated tissues such as

adipose tissue, bone tissue and cartilage tissue.

1.2. Mesenchymal Stem Cells

The notion of the mesenchymal stem cells (MSCs) was suggested by Maureen

Owen by considering the first experimantal findings about fibroblast-like colony

forming cells of bone marrow of Alexander Friendestein and his colleagues in mid

60’s. In early 1990’s Arnold Caplan proposed that MSCs were fibroblast like

adherent cells (Figure 1.1) isolated by fractionation on a density gradient solution

ficoll. Especially, in last two decades there was an increasing interest on MSCs

studies from different research groups that they were trying to clarify MSCs

characteristics to accelerate basic scientific investigations and for further clinical

studies of MSCs. In 2000, a report was published by International Society for

Cellular Theraphy (ISCT) to define scientifically accurate MSCs identity mainly

for laboratory based research purposes by universially accepted standarts.

3

According to ISCT recommendations; MSCs have to be adherent to plastic

surfaces when cultivated in appropriate complete media, they must express CD73,

CD90 and CD105 surface antigens while they lack expression of CD34, CD45 and

finally they have to have capacity differentiate to osteaoblast, adipocytes and

chondroblasts using specific in-vitro inducing media (Horwitz et al., 2005;

Dominici et al., 2006).

1.2.1. Characteristics of Mesenchymal Stem Cells

MSCs which are non-hematopoietic, stromal cells found primarily in bone marrow

stroma and other to many human tissues (Jackson et al., 2007). MSCs of the bone

marrow (BM) provide cellular microenvironment to support maintanance of

hematopoietic stem cells’s growth and differentiation (Jackson et al., 2007; Kemp

Figure 1.1 Mesenchymal stem cells. “a) Monolayer of rapidly expanding adherent spindle-shaped fibroblastoid cells compatible with undifferentiated mesenchymal stem cells (×100) b) Cell cluster of rapidly expanding adherent spindle-shaped fibroblastoid cells compatible with undifferentiated mesenchymal stem cell morphology (×100)” (Adopted from Koch et al., 2007 with permission).

4

et al., 2005). BM can be collected from posterior iliac crests of pelvis and then

mononuclear cells (MNCs) are harvested from BM with a density gradient

isolation procedure with ficoll (Pittenger et al., 1999). A small fraction of (0,01-

0,0001 %) isolated MNCs adhere to the plastic surfaces in culture and expand as

fibroblast like cells that are considered as the primary ex-vivo source of

mesenchymal progenitor cells (Pittenger et al., 1999; Minguell et al., 2001;

Jackson et al., 2007).

1.2.1.1. Phenotype of Mesenchymal Stem Cells

There is a considerable interest on definition of MSC phenotype to be able to

accomplish characterization, purification and further analysis of MSCs. Recent

studies has shown the availibility of an expression of several cell surface antigens

and monoclonal antibodies in BM-MSCs (Aerts, 2004; Dennis and Caplan, 2004).

Human MSCs don’t express main hematopoietic antigens called as CD14, CD34

and CD45 (Baksh et al., 2004). The monoclonal antibodies SH2, SH3 and SH4 are

raised against human MSCs (Barry, 2003). SH2 antibody binds an epitope on

endoglin (CD105, a receptor for tranforming growth factor βI and βIII). SH3 and

SH4 antibodies recognize different region of antigenic epitopes on the membrane

bound ecto-5-nucleotidase that known as CD73 surface antigen expressed by

MSCs. The SB10 antibody reacts with activated leukocyte-cell adhesion molecule

(ALCAM; CD166). The monoclonal antibody Stro1 is specific for clonogenic BM

stem cell progenitors in human bone marrow. In order to characterize phenotype of

MSCs and to enrich MSCs from mixed cell population, the combination of

antibodies have to be used (Aerts, 2004; Kemp et al., 2005). MSCs also express

cell adhesion molecules like ICAM-1, integrin α4, α5 and β1, ανβ3 and ανβ5

and CD44H. MSCs express extracellular matrix molecules such as collagen

fibronectin, laminin, and proteoglycans which clarify and strengthen the

5

suggestion about an important and dynamic role of MSCs in the BM during

development of stromal marrow microenvironment. The several counter receptors

required for cell-matrix and cell-to-cell direct interactions are also expressed by

MSCs (Minguell et al., 2001).

1.2.1.2. Production of Cytokines and Growth Factors

MSCs, which have capabilities of self-renewal and differentiation into different

lineages of mesenchym tissues, need secretion and regulation of specific growth

factors, cytokines and chemokines in a lineage or stage specific manner (Dormady

et al., 2001). The variability of secretion profile of MSCs provide therapeutic

effects of them (Zhukareva et al., 2010). BM-MSCs produce an extended profile

of growth factors and cytokines, which have significant role in the regulation of

hematopoiesis (Majumdar et al., 2000). Primary stromal cell cultures or in stromal

cell lines secrete Granulocyte-Colony Stimulating Factor (G-CSF), GM-CSF, M-

CSF, Interleukin-1 (IL-1), IL-3, IL-6, IL-7, IL-8, IL-11, IL-12, IL-14, IL-15, LIF,

fibroblast growth factor (FGF), stem cell factor (SCF), Flt-3 ligand (FL), and

tumor necrosis factor (TNF) (Dormady et al., 2001; Majumdar et al., 1998;

Harneysworth et al., 1996; Thalmeier et al., 1996).

1.2.1.3. Differentiation Capacity of Mesenchymal Stem Cells

Differentiation ability of bone marrow mesenchymal stem cells into osteocytes

was firstly discovered by Friedenstein et al., 1966. Then Pittenger et al., 1999

mentioned about differentiation potential of human mesenchymal stem cells into

lineages of mesenchymal tissues, like bone, cartilage, fat, tendon, muscle and

marrow stroma. However; recent studies have shown that bone marrow

mesenchymal stem cells (BM-MSCs) have multilineage differentiation capacity

with their differentiation into mesodermal and non-mesodermal cell lineages (Yan

6

et al., 2010). As it is seen in Figure 1.2, BM-MSCs can differentiate into not only

osteocytes, adipocytes, chondrocytes but also myocytes, cardiomyocytes,

fibroblasts myofibroblasts, epithelial cells and neurons (Liu et al., 2009).

Miyogenic differentiation of MSCs was determined by myotube formation (Beier

et al., 2010; Yan et al., 2010) and induction and differentiation of BMMSCs into

cardiomyocyte-like cells. The in-vitro differentiation of BM-MSCs into neuron-

like cells was explained by not only expression of neuron phenotype and

membrane channel protein including Nav1.6, Kv1.2, Kv1.3 and Cav1.2 but also

exhibited functional ion currents (Zeng et al., 2011). BM-MSCs have also capacity

to differentiate into renal (Asanuma et al., 2010) of kidney and also hepatic cells

of liver (Mohsin et al., 2011).

Figure 1.2 “The mesengenic process. The stepwise cellular transition from the putative mesenchymal stem cell (MSC) to highly differentiated phenotypes are depicted schematically” (Adopted from Caplan, 2009 with permission).

7

1.3. Clinical Usage of Mesenchymal Stem Cells

Human MSCs with their multilineage differentiation ability and self renewal

capacity have great potential as a source of cells for cellular therapies in

regenerative medicine and for tissue engineering approaches (Baksh et al., 2004).

Autologous or allogenic stem cells may be transplanted into patients during stem

cell therapy, therefore; the use of MSCs in clinical applications requires

standardization and quality control of each step from isolation to transplantation

(Wagner et al., 2010). BM-MSCs provide housing for HSCs and enhance their

engraftment after HSC transplantation (Lazarus et al., 2005) which has been used

for some years in the treatment of leukemia and other cancers (Tabbara et al.,

2002). MSCs carry the potential for use in treatment of injury in different diseases

including cardiovascular repair, coronary artery disease (Stamm et al., 2003),

treatment of lung fibrosis, spinal cord injury and bone and cartilage repair (Barry,

2003). Implemantation of stem cells with the ability to differentiate into neurons

and neural stem cells in an adult rat model of spinal cord injury resulted in long-

term functional healing (Teng et al., 2002). It was shown in rat models that MSCs

may be useful in the treatment of stroke, traumatic injury and Parkinson’s Disease.

MSCs can also be used in the area of orthopedic medicine for the repair of

segmental bone defects (Quarto et al., 2001) and craniotomy defects (Krebsbach

et al., 1998), and for repair of focal defects in articular cartilage (Ponticiello et al.,

2002) and tendon (Young et al., 1998).

1.4. Mesenchymal Stem Cells as a Main Cellular Component of the Bone

Marrow Microenvironment and Hematopoiesis

The bone marrow microenvironment contains both mesenchymal and

hematopoietic stem cells. This microenvironment is the main site of hematopoiesis

during the development of any types of blood cells (Gordon, 2010). The other cell

8

types such as osteoblasts, adipocytes and endothelial cells have an important roles

throughout the regulation of normal and malignant mechanisms in hematopoiesis

(Walkley, 2011). “It has been well established that some hematopoietic diseases

can dramatically affect the composition or function of certain cell types of the BM

microenvironment, and that this in turn may further contribute to the severity of

the hematopoietic disease” (Askmyr et al., 2011). “Thalassemia represents an

extreme example of chronic anemia associated with changes in the bone marrow

microenvironment” (Walkley, 2011).

1.5. What is Thalassemia?

Thalassemia is an inherited blood disorder. The defect in the globin gene causes

unsufficient production of hemoglobin molecule that leads to anemia as a result of

excessive destruction of red blood cells. Hemoglobin which is an oxygen carrying,

tetrameric, globular protein composed of four globin chains. The most well known

adult hemoglobin molecule is called as Hemoglobin A consisting of 2β and 2α

globin chains (Figure 1.3). Thalassemia results from a genetic mutation in alpha or

beta globin molecule that causes non or reduced production of mutated globin

chain while unmutated globin chain accumulates in red blood cells (Lanzkowsky,

2000).

Thalassemias are characterized according to type of deficient globin chain. The

missing or mutated alpha genes related with the absence or reduced synthesis of

alpha (α) globin protein that give the name to the disease as alpha thalassemia. If

similar genetic defect affects the genes of beta (β) globin protein, the disease is

called as beta thalassemia (Mader, 1997). Alpha thalassemias are observed

commonly in people from South Asia, Malaysia, and Southern China, while beta

thalassemias generally are seen in people from Mediterranean origin, Africa and

9

other Asia countries. Thalassemia has been started to be seen since ten years in

America, because of the huge migration potential of America (Loukopoulos et al.,

1991).

The severity of disease is defined according to the number of mutated genes in

globin protein. If inherited defective gene(s) comes from both mother and father,

the disease called as thalassemia major. However, thalassemia minor occurs when

the defective gene(s) comes from only one parent. People who have thalassemia

minor become a carrier of the disease, however they usually do not have disease

symptoms (Lanzkowsky, 2000).

Figure 1.3 The structure of hemoglobin (Adopted from Mader, 1997 with permission).

10

1.5.1. Beta Thalassemia Major

Beta thalassemia is an autosomal recessive blood disease with diminished

production of hemoglobin that leads to hemolytic anemia. In order to make

sufficient beta globin chains, two genes are required. If one or both of these genes

are mutated beta thalassemia occurs. The severity of beta thalassemia and resulting

anemia depends on the number of genes that are affected from mutations. If one

gene is abnormal, the disease is known as beta thalassemia trait that is associated

with reduced beta globin chain which does not cause great problem in the normal

functioning of hemoglobin molecule. When two genes are mutated the more

severe form of beta thalassemia which is called as beta thalassemia major (β-TM)

or Cooley’s anemia are seen. The severe decrease or complete lack of beta globin

synthesis prevents the production of Hemoglobin A that causes life-threatening

anemia after three months of age. Survival of patients with this severe anemia

depends on lifelong regular blood transfusions that lead iron accumulation in vital

organs of the body such as liver and heart (Olivieri, 1999; Lanzkowsky, 2000;

Birgens and Ljung, 2007).

1.5.2. Ineffective Erythropoiesis

The inbalanced synthesis of β-globin chains leads to accumulation of excess α-

globin chains in red blood cells. The aggregation of α-globin chains produces

precipitates that cause cell hemolysis by destroying red cell membranes and results

with destruction of erythroid precursors in bone marrow termed. This is called as

ineffective erythropoiesis (IE). In thalassemia, IE is characterized by apoptosis and

limited differentiation of erythroid cells. Overall erythropoiesis in BM and spleen

increases impressively during ineffective erythropoiesis conditions. However, such

an increased erythropoietic activity can not prevent intramedullary and intrasplenic

11

death of erythroid precursors. This condition is often coupled with a dramatic

expansion of the bone marrow to get rid of exarcerbation of deep anemia and iron

accumulation (Melchiori et al., 2010). Changes of oxygen tension occur in tissues

due to anemia which is associated with a rise in erythropoietin (EPO) level in

order to compansate for anemia. EPO serves as the main regulator of all stages of

erythroid differentiation, proliferation, and maturation during profound anemia

(Fang et al., 2007). Increased EPO levels drive an uncontrolled expansion of

erythroid precursors with an enhanced proliferative and survival capacity.

However, these cells fail to differentiate into mature red blood cells, therefore

severe anemia can not be ameliorated by excess production of erythroid precursors

in bone marrow which leads ineffective erythropoiesis (Libani et al., 2008).

GDF15 is a protein of transforming growth factor-β (TGF-β) superfamily which is

involved in several processes like cell differentiation, development and apoptosis

(Whitman et al., 1998). Since the expression of GDF15 is generally associated

with apoptosis, serum GDF15 levels increases in many types of hematological

diseases associated with ineffective erythropoiesis such as thalassemia (Tanno et

al., 2010). Imbalance in the production of α- and β-globin chains cause apoptosis

of erythroblasts during which severe ineffective erythropoiesis and extreme bone

marrow expansion are combined as a result of anemia (Schrier et al., 2002).

Meanwhile, GDF15 is overexpressed and secreted from erythroblast as a member

of bone morphogenic protein family, also contributes to the severe bone

abnormalities of thalassemia. Therefore, elevated GDF15 levels in serums of β-

thalassemia patients is used as a biomarker of the disease (Tanno et al., 2007).

1.5.3. Hematopoietic Stem Cell Transplantation Therapy in Beta Thalassemia

Major

The standard blood transfusion therapy in order to sustain life of thalassemic

patients causes development of splenomegaly and also dramatic iron overload in

12

tissues. Excessive iron accumulates in vital organs like liver, heart, endocrine

glands. Therefore; iron overload is one of the major reason of death in thalassemia

patients. (Melchiori et al., 2010). In order to improve the quality of life of

thalassemic patients and to prevent undesired effects of iron accumulation, iron

chelation therapies are applied. Aggressive blood transfusions and iron chelation

are expensive and life-long therapies with significant morbidity Allogeneic

hematopoietic stem cell transplantation (HSCT) from an HLA-compatible family

donor has been accepted as the most effective therapy of thalassemia major since

30 years (Aggarwal et al., 2003). HSCT in thalassemia major replaces IE with an

effective allogeneic hematopoietic cell substitute to obtain permanent, effective

healing of the hemolytic anemia (Angelucci and Baronciani, 2008)

Chimerism analysis after bone marrow transplantation (BMT) is used to determine

genotypic origin of bone marrow cells. It has been shown that full donor

chimerism is usually achieved in hematopoetic cells after transplantation.

However, BM-MSCs remain of host origin post-transplant (Rieger et al., 2009;

Bartsch et al., 2005) The normal MSC content of bone marrow is about 0.01 to

0.05% of mononuclear cells (Minguell et al., 2001). The limited MSCs content of

bone marrow could explain why after bone marrow transplantation, MSC of donor

origin could not be detected.

1.6. HSC and MSC Interactions in Bone Marrow Microenvironment: Stem

Cell Niche

Stem cells (SCs) are located in highly regulated, complex and multifactorial

microenvironment defined as niche. A stem cell niche is required for the

maintenance of balance between self-renewal and differentiation. There is constant

dialog between SCs, non-SCs, an extra cellular matrix and molecular signals in the

niche to control stimuli for differentiation and self-renewal (Becerra et al., 2011;

13

Mitsiadis et al., 2007). The control and regulation of SCs and interactions with

their niche are important in terms of cell therapy and regenerative medicine for

gaining of basic understanding of stem cell applications into clinical medicine

(Becerra et al., 2011).

Hematopoietic stem cells are localized in two different niches in the bone marrow.

The locations are called as an “endosteal niche” and a “perivascular niche”

(Mitsiadis et al., 2007). Interaction between HSCs and their niches provide

maintanance and balance for their differentiation, self-renewal and quiescence.

Therefore, the location of HSCs are determined according to the their lineages and

hierarchical positioning. While undifferentiated HSCs are mainly found in the

endosteal region, hematopoietic progenitors are generally located in central

(vascular) bone marrow regions (Kiel and Morrison, 2006).

Hematopoietic stem cell transplantation has gained great importance for the

treatment of hematologic malignancies and non-malignant disorders. Several

research groups have focused on ex vivo expansion of HSCs in order to improve

the clinical outcome of autologous and allogeneic HSC transplantation (Jing et al.,

2010). In this context, understanding of factors contributing the maintanace of

HSCs in their niches has been recently investigated and the existing studies

showed that MSCs facilitate HSCs maintenance through the secretion of soluble

factors and cell-cell contact (Wagner et al., 2007). Therefore; investigation of

interactions between HSCs with MSCs will provide an information in order to

understand in-vivo regulation of hematopoietic stem cells and to design stem cell

based cellular therapies (Purton and Scadden, 2011).

14

1.7. Aging of Stem Cell Niches and Intrinsic Aging of Mesenchymal Stem

Cells

Adult stem cells in specific organ systems are required for the maintenance and

repair of these organs throughout adult life. This funcion of stem cells is regulated

by molecular signaling to ensure proper cellular, tissue and organ homeostasis, but

how this coordination changes with aging is mostly unknown (Drummond-

Barbosa, 2008). The reciprocal interactions between stem cell aging on tissue

homeostasis and aged cellular microenvironment on stem cells will be critical to

the success of any therapeutic application of stem cells in the emerging field of

regenerative medicine (Rando, 2006; Drummond-Barbosa, 2008; Greco and

Rameshwar, 2008).

The process of MSC aging is important because of their role in tissue regeneration

and repair. For the success of clinical application and for desired therapeutic

outcome, the impact of aging on stem cells have to be understood (Wilson et al.,

2010). Existing studies have focused on the effect of aging on the differentiation

ability or the changes in the number of MSCs. Some, but not all studies showed

that aging reduces osteogenesis, chondrogenesis and adipogenesis (Moerman et

al., 2004; Zheng et al., 2007; Tokalov et al., 2007) and they also showed decreases

in the number of MSCs in the bone marrows of rodents, monkeys and humans.

Recent studies in the literature observed that MSCs of older donors showed

decreased proliferation potential and increased senescence when compared with

the cells of younger donors (Vacek, 2000; Stenderup et al., 2003; Baxter et al.,

2004; Mareschi et al., 2006).

Recent studies suggested that aging can be related with decrease in the number and

function of stem cells. However, causal relationships is largely unknown. In other

words, there are some questions to be answered; does aging lead to decline in stem

15

cell number or does stem cell decline lead to aging? Despite available information,

little is known about how and why MSCs age in vivo. The effects of donor age in

regenerative medicine and in-vivo use for damage healing has not been

investigated well. It is thougth that donor age can be effective parameter to obtain

most efficient recovery. Stem cells can differentiate into many different cell types

and the determining of molecular changes depending on the donor age in the stem

cells have great importance in terms of regenerative medicine to select donor for

therapeutic purposes. These recent knowledge will contribute development of in

vitro conditions for stem cell based clinical applications. Characterization of

interactions of cellular, biochemical and molecular interactions between MSCs and

their microenvironment will contribute to understand in vitro control of them.

1.8. Optical Spectroscopy

1.8.1. Basis of the Spectroscopy

A spatially-varying electric field generates time-varying magnetic field which

oscillate mutually perpendicular in a single plane to form electromagnetic

radiation. Figure 1.4 shows these fields as a sine wave with their direction of

propagation (Stuart, 1997).

The interaction between electromagnetic radiation and matter redirect radiation

between energy levels of the atoms or molecules. This interaction can be in

various manners like absorbtion, scattering, reflection, emission etc. When the

light is absorbed, chemical bonds vibrate and intermolecular distance of two or

more atoms changes. This is called as vibrational energy which is resulted from

excitation of an atom to an upper energy level in accordance with the wavelength

of the light (Freifelder, 1982). An excited atom or molecule can have any one of a

set of unique amounts of energy which are called as the energy levels of the

16

molecule. The energy levels are usually described by an energy level diagram

shown in Figure 1.5.

The total energy of a molecule is composed of several distinct reservoirs of energy

as it is given by the following equation (Campbell and Dwek, 1984).

Etotal=Etranslation+Erotation+Evibration+Eelectronic+Eelectronicspinorientation+Enuclearspin orientation

In this equation, each E that is represented by its subscript reflects the appropriate

energy level. The separations between the neighboring energy levels

corresponding to Erotation, Evibration and Eelectronic are associated with the microwave,

infrared and ultraviolet-visible regions of the electromagnetic spectrum,

respectively (Campbell and Dwek, 1984).

Figure 1.4 Electromagnetic wave

17

When the specific vibration with an equal frequency of IR radiation moves on the

molecule, the molecule absorbs the energy of radiation by transitions induced

between different energy states of the molecules in the sample. Absorption is most

probable when the energy level separation matches the energy of the incident

radiation as indicated below,

∆E=hν

where ∆E is the dispertion between the energy states of sample, ν is the frequency

of the applied radiation and h is Planck’s constant (h = 6.6x10-34 joule second),

Figure 1.5 “Energy level diagram illustrating the ground and first excited electronic energy level. Vibrational energy levels are represented as parallel lines superimposed on the electronic levels. The long arrows show a possible electronic transition from the ground state to the first excited state while the short arrow represents a vibrational transition within the ground electronic state” (Freifelder, 1982).

18

c = λ ν

c is the speed (3.0x108 ms-1) and λ is the wavelength of light. From these two

equations we can derive wavenumber, which is presented by ν, reciprocal with the

wavelength (λ). Wavenumber means the number of waves per unit length, so it is

directly proportional to frequency, as well as the energy of the IR absorption.

Wavenumber is defined as in the below interconvertion;

ν = wavenumber = (1/ λ) [ has a unit of cm-1]

Thus, IR absorption positions are shown with wavenumbers ( ν ) or wavelengths

(λ). In contrast, wavelengths are inversely proportional to frequencies and their

associated energy.

E = h ν = h c (1/ λ ) = hcν,

The study of interaction of electromagnetic radiation with matter is called as

spectroscopy. Spectrum is defined by a plot of the energy absorbed (E =hν ) as a

function of wavelength or more commonly frequency. The electromagnetic

spectrum ranges from the shorter wavelengths (including gamma and x-rays) to

the longer wavelengths (including microwaves and broadcast radio waves) (Figure

1.6). Light can interact with sample with some form of electromagnetic radiation

like scattering, absorption, or emission. The determination of radiation in terms of

some measured parameters and the interpretation of these measured parameters

generates the basis of spectroscopic techniques.

19

1.8.2. Infrared Spectroscopy

The region between 14.000 cm-1 and 4 cm-1 of the electromagnetic spectrum is

called as infrared region which is divided three sub-regions as near-infrared region

(14.000 cm-1 to 4.000 cm-1), mid-infrared region (4.000 cm-1 to 400 cm-1) and far-

infrared region (400 cm-1 to 4 cm-1). The infrared applications related with

biological samples use mid infrared region of the electromagnetic spectrum. The

IR spectroscopy works on the basis of determination of the chemical functional

groups in the sample according to their unique absorbtion charactheristics.

Therefore, the infrared spectrum can be used as a fingerprint for identification of

unknown molecule by comparing it with known reference spectra (Hsu, 1997).

The molecular atoms oscillate constantly around average positions. The chemical

bonds and the intramolecular distance between two or more atoms changes when

the IR radiation is absorbed by the molecule. When the change in the dipole

Figure 1.6 The Electromagnetic Spectrum

20

moment, which occurs during charge separation across the bond, is accompanied

by the vibration, the molecule can absorb IR radiation. The oscillations of the

atoms can be defined in terms of two types of molecular vibrations as stretching

and bending. Stretching is a symmetric or antisymmetric rhythmical movement

along the bond axis. The bending vibration occurs when the bond angle change.

These motions are also called as scissoring, wagging, rocking, and twisting (Figure

1.7).

The infrared spectroscopy is a useful chemical analytical method, because each

different material has a unique chemical structure and therefore each molecule has

a different wavenumber which is correlated with its chemical structure. This

means that two compounds create different infrared spectrum like their chemical

fingerprints. This makes infrared spectroscopy available for identification of

Figure 1.7 “The schematic representation of some molecular vibrations in linear triatomic molecules (A) and non-linear triatomic molecules (B). (+) and (–) symbols represent atomic displacement out of page plane” (Arrondo et al., 1993).

21

unknown materials, determination of quality or consistency of a sample and

determination of the amount of components in a mixture, ect.

1.8.2.1. The Fourier Transform Infrared Spectroscopy (FTIR)

Fourier transform infrared (FTIR) spectroscopy has found increasing interest by

the invention of Michelson interferometer (Figure 1.8) since early eighties.

Michelson interferometer produces an interferogram by spliting an

electromagnetic radiation between two directions and then by recombining the

intensity variation which can be determined as a function of the path difference

between them. The interferometer contains two orthogonal mirrors: one movable

and the other fixed. The light passes through a beam splitter, which sends the light

in two directions at right angles. One beam goes to a stationary mirror then back to

the beam splitter. The other beam goes to a moving mirror. The motion of the

mirror makes the total path length variable versus that taken by the stationary-

mirror beam. When the two meet up again at the beam splitter, they recombine,

and the difference in path length creates constructive and destructive interference,

which is called as an interferogram. The recombined beam passes through the

sample. The sample absorbs all the different wavelength characteristics of its

spectrum. The detector now reports variation in energy absorbed or transmitted

versus time for all wavelengths simultaneously. A laser beam is superimposed to

provide a reference for the instrument operation.

Energy versus time is an odd way to record a spectrum until it is recognized the

relationship between time and frequency was recognized: they are reciprocal. A

mathematical function called Fourier transform allows us to convert an intensity-

versus-time spectrum into an intensity-versus-frequency spectrum. The

spectrometer computer is able to deconvolute (Fourier Transform) all the

22

individual cosine waves that contribute to the interferogram and so produce a plot

of intensity against wavelength (cm-1), or more usually frequency (cm-1).

1.8.2.1.1. Advantages of FTIR Spectroscopy

• It is rapid and sensitive technique which enables to make measurements

within seconds and reduce the noise levels (Hsu, 1997).

Figure 1.8 Schematic representation of a Michelson Interferometer.

23

• FTIR spectrometers are self-calibrating and never need to be calibrated

externally (Rigas et al., 1990)

• It is a non-invasive and non-destructive technique (Melin et al., 2000;

Severcan et al., 1999; Cakmak et al., 2003).

• It is a low cost technique.

• FTIR can analyze small quantities of samples (Mendelsohn et al., 1986).

• It can be applied to any kind of materials in different physical states such

as solutions, viscous liquids, suspensions, inhomogeneous solids or

powders (Colthup et al., 1975).

• It gives valuable information about the biological samples by detecting

changes in the functional groups belonging to the tissue components such

as lipids, proteins, carbohydrates and nucleic acids, simultaneously

(Kneipp et al., 2000; Bozkurt et al., 2007; Garip et al., 2007).

• The specific computer based softwares for FTIR spectrometers enable to

make data storage and data processing (Yono et al., 1996; Ci et al., 1999).

Digital substraction is used to obtain good difference spectra especially for

infrared spectra of aqueous solutions (Campbell and Dwek, 1984).

• The shifts in the band frequencies and changes in the bandwidth, and band

area/intensity values provide valuable informations that are correlated with

the alterations in the structure and composition of macromolecules. These

informations can be used as a diagnostic tool for the analysis of cell

components, tissue sections, biofluids and so on. So that, FTIR

spectroscopy has become mostly preferable method for biomedical

diagnosis, recently (Liu et al., 1996; Yano et al., 1996; Schultz et al., 1998;

Ci et al., 1999; Dicko et al., 1999; Severcan et al., 2000; Toyran et al.,

2004; Akkas et al., 2007a; Akkas et al., 2007b; Szczerbowska-

Boruchowska et al., 2007).

24

• Recently, FTIR spectroscopy has become a promising tool in biomedicine

for diagnosis and discrimination of characteristic molecular changes

between normal and disease states, especially in different cancer types

(Argov et al., 2002; Babrah et al., 2009). This technique is also used in the

analysis of cytotoxic effects of radiation in radiobiology, taxonomical

stuies in microbiology (Dogan et al., 2007; Garip et al., 2007) and plant

studies (Gorgulu et.al., 2007), the discrimination of drug resistant and drug

sensitive cancer cells, the examination of apoptosis (Gaigneaux et al.,

2006; Sahu et al., 2006) and the determination of stem cell differentiation

into adipogenic, osteogenic and neurogenic cells (Aksoy et.al., 2012;

Tanthanuch et al., 2010; Downes et al., 2010; Ishii et al., 2007).

1.8.2.1.2. Attenuated Total Reflectance Fourier Transform Infrared (ATR-

FTIR) Spectroscopy

ATR-FTIR spectroscopy works on the basis of total internal reflection

phenomenon. When the infrared beam, which is directed onto an optically dense

crystal with a high refractive index, passes through an ATR crystal at a certain

angle, it is internally reflected that causes creation of evanescent wave protruding

only a few micrometers beyond the surface of ATR crystal. If the refractive index

of sample be slower than that of the crystal, the light will be transmitted rather

than internal reflectance. Although the extention of the evenescent wave depends

on the type of crystals being used, the wave can protrude maximum between 0.5 µ

-5 µ beyond the surface of the crystal into the sample. There are many kinds of

materials used for ATR crystal such as diamond, amorphous material transmitting

IR (AMTIR), germanium and silicon, however; the mostly used one is zinc

selenide (ZnSe). ZnSe which is water resistant, cost effective and easly cleanable

material for ATR. The distance that the wave extends from the crystal surface is

25

about 1.66 µm for ZnSe ATR crystal. The radiation that penetrates a fraction of a

wavelength beyond the surface of the crystal enters the sample that is placed on its

surface and therefore, there must be complete contact between sample and crystal

surface (Figure 1.9 and Figure 1.10) (Perkin Elmer Life Sciences, 2005; Kazarian

et al., 2006).

ATR is very applicable technique to different kinds of samples. A solid sample can

be directly placed on ATR crystal with a pressure to obtain best contact for reliable

FTIR spectra, while aqueous samples can be placed on crystal with a volume of a

few microliters appropriate with their concentration. However cells are deposited

onto crystal by evaporating the cell suspension buffer by nitrogen flux to obtain

cell film (Peak, 2004). In the cell studies absolute absorbance can change as a

Figure 1.9 ZnSe Diamond ATR attachment of Perkin Elmer Spectrum 100 FTIR

spectrometer.

26

results of variation in the cell density, because the distribution of cells on the ATR

crystal can not be adjusted accurately during cell film preparation. Therefore,

absolute absorbance variation is usually corrected by the scaling of all spectra to

be compared. The usual scaling criteria is the setting of the maximum absorbance

of Amide I peak to 1 (Gaigneaux et al., 2006) Attenuated Total Reflection (ATR)

mode of FTIR spectroscopy has wide range of application area like discrimination

of normal and disease states (Bozkurt et al., 2010; Khanmohammadi et al., 2007),

biodiagnostics and cell line classification (Ozek et.al., 2010; Gaigneaux et al.,

2006), investigation of cellular activation (Timlin et.al., 2009), characterization of

stem cells in disease and healthy states (Aksoy C et.al., 2012), fingerprinting of

microorganisms (Winder et al., 2004) and detection of microbial products (Bullen

et al., 2008; Leitermann et al., 2008), structural analysis of proteins (Goldberg and

Chaffotte, 2005).

Figure 1.10 Schematic representation of ATR top plate (Perkin Elmer TCH

material)

27

1.8.2.2. Fourier Transform Infrared Microspectroscopy

Fourier transform infrared (FTIR) microspectroscopy can be defined as a

combination of an infrared spectroscopy with a microscope (Figure 1.11). FTIR

microspectroscopy allows the detection of chemical species from a spatial region

by combining spatial specificity with information on its chemical constitution.

“The integration of a microscope into the FTIR spectrometer enables it to be used

in an imaging mode to create micron-scale chemical maps of a multicomposite

sample like single cell. This can be achieved by using a single point detector with

an adjustable sampling aperture to define an area on the cell from which the

spectral data can be acquired. The cell is then moved in small increments that

complement the sampling aperture size, with an IR spectrum recorded at each

increment, resulting in the IR chemical map. Thus, the lateral resolution of the IR

map is defined by the sampling aperture size” (Gazi et al., 2005). Compared to

standart methods of histology, cytology and biomedical microscopy, IR spectral

imaging offer the adventage of probing biochemical nature of cells with minimal

sample preparation and without the use of dyes, stains and flourescent agents

(Bechtel et al., 2009; Diem et al., 2004; Romeo et al., 2008).

IR microspectroscopy of biological systems is a developing area to investigate

cells in different stages such as their growth cycles (Matthaus et al., 2006),

cancerous states (Dukor, 2002), contaminated states with pathogens

(Erukhimovitch et al., 2003). IR microspectroscopy applications can be performed

in transmission or reflection mode according to the optical properties of the sample

(Bechtel et al., 2009). In transmission mode, sample or substrate are placed on an

IR transparent microscope slides such as barium floride (BaF2), calcium floride

(CaF2), ZnSe glass slides. In reflection mode measurements gold or silver coated

substrates are used. In recent studies “low-e slides” of Kevley Technologies are

used in transflection measurement. Low-e slides, coated with this silver tin oxide

28

(Ag/SnO2), are made of glass and they are similar dimension to traditional glass

microscope slides. The slides are chemically inert and nearly transparent to visible

ligth; however, mid infrared radiation is almost completely reflected. The ligth

beam passes through the sample to the substrate, reflects off the silver surface, and

passes through the sample a second time (Romeo et al., 2008). Sample preparation

for microspectroscopic investigation of individual cells is composed of several

steps as attachement of cells onto microscopic slides, fixatition of cells on slide,

washing of fixed cells and drying. These steps were expressed as in methodology

chapter.

Figure 1.11 Perkin Elmer Spectrum Spotlight 400 imaging FTIR

microscope.

29

1.8.3. Infrared Spectroscopy in Stem Cell Researches

Over the last few years, there has been increased interest of biomedical

applications of stem cells in therapeutic and regenerative medicine because of their

significant role in tissue renewal and homeostasis with their unique capacity to

differentiate into cell types. Such an inceasing interest on the therapeutic usage of

stem cells, bring with its challenges, that have to be addressed before cell-based

clinical applications, such as isolation, identification, purification and enrichment

of stem cells (Pijanka et al., 2010; Chan et al., 2009). Identification of purity and

differentiation stages of stem cells are greatest challanges of stem cell biology and

regenerative medicine. The existing methods to carefully monitor and characterize

the stem cells have some unwanted effects on the properties of stem cells and these

methods also do not provide real-time information about cellular conditions. These

challanges enforces the usage of non-destructive, rapid, sensitive, high quality,

label-free, cheep and innovative chemical monitoring methods. Commonly used

biological assays for stem cell analyses like fixation, staining and drying do not

provide real time information and destroy cellular characteristics (Konorov et al.,

2011). Therefore, the development of new methods that are available to collect

real-time biochemical information about living stem cells is important for clinical

studies in regenerative medicine (Moody et al., 2010). Some spectroscopic

methods can be successfully used to characterize the biochemical make-up of

intact live stem cells in non-destructively and label-free manner (Pijanka et al.,

2010; Konorov et al., 2011). IR spectroscopy is complementary, label-free, non-

invasive and non-destructive vibrational spectroscopic techniques in which the

optical signals is generated intrinsically from the sample to obtain information

about relative concentrations and structure of macromolecules such as protein,

lipids, carbohydrates and nucleic acids (Krafft et al., 2006; Diem et al., 2008). IR

spectroscopy is very attractive method because of its great potential to identify

similarities and differences between stem cell populations and stem cell lineages,

30

and the level of maturation and differentiation of stem cells, by determining their

unique optical markers (Chan et al., 2009).

Cells and tissues give complex infrared spectra with their complex biological

nature. The infrared spectrum of cells and biological tissues is composed of

summation of proteins, lipids, carbohydrates, sugars and nucleic acid

contributions. Each component is assigned with a characteristic absorbtions in the

mid-infrared region (4000–400 cm-1). The bands observed in within the 3000–

2800 cm-1 region are resulted from the symmetric and antisymmetric stretching

vibrations of CH2 (2852 and 2922 cm-1) and CH3 (2874 and 2956 cm-1),

respectively (Mantsch, 1984; Severcan et al., 2000; Severcan et al., 2003, Cakmak

et al., 2006). The strong absorbtion band located 1735 cm-1 is associated with the

C=O stretching vibration of ester groups. The frequency of this band is strongly

affected by hydration (Melin et al., 2000; Cakmak et al., 2003; Severcan et al.,

2003). The most intense absorption bands are observed in 1800-800 cm-1 region.

The band at 1650 cm-1 is attributed mainly from the C=O stretching vibration of

the amide C=O group and is termed as the amide I band. The frequency of this

band can be used detailed analysis of conformation of the protein secondary

structure. Another amide mode of protein spectra is the amide II absorption band

that is located between 1500–1560 cm-1 is associated with the N– H bending

vibrations and the C–N stretching vibrations of proteins. Additional bands which

are found at 1580 and 1400 cm-1 are assigned to the COO- symmetric and

antisymmetric stretching vibrations, respectively. These absorptions are related

with the amino acids aspartate and glutamate (Manoharan et al., 1993, Haris and

Severcan, 1999). Small numbers of very weak bands are observed between 1500–

1250 cm-1 region. The most distinct band is located at 1452 cm-1 which is

characteristic of the CH2 bending vibration (Cakmak et al., 2003; Di Giambattista

et al., 2011) and COO− symmetric stretching vibrations of fatty acid and amino

acid side chains, at around 1400 cm−1 (Peuchant et al., 2008; Cakmak et al., 2006;

31

Melchiori et al., 2010). There are two intense bands due to the symmetric and

antisymmetric vibrational modes of phosphate groups (PO2-), respectively. These

are associated with the phosphodiester linkages of the polynucleotide chain and

are assigned to symmetric (1085 cm-1) and antisymmetric (1225 cm-1) phosphate

stretches. The frequency of these bands can provide information into head-group

hydration (Rigas et al., 1990; Wong et al., 1991; Wang et al., 1997; Cakmak et al.,

2003). Carbohydrates give rise to strong bands between 1200 and 1000 cm-1. The

band at 1152 cm-1 is due to stretching mode of the CO-O-C groups present in

glycogen and nucleic acids (Rigas et al., 1990; Cakmak et al., 2003). The bands at

1025 and 1045 cm-1 are attributed to the vibrational frequency of CH2OH groups

and the C-O stretching frequencies coupled with C-O bending frequencies of the

C-OH groups of carbohydrates (including glucose, fructose, glycogen, etc.)

(Parker, 1971). The main absorption bands found within mammalian cells and

tissues are displayed in band assignment table (Table 3.1).

1.9. Aim of the Study

Stem cell studies hold enormous potential for development of new therapies.

Investigation of stem cells in normal developmental and physiological state as well

as in pathological conditions may lead to understanding of disease pathogenesis

and development of cellular therapies.

Bone marrow mesenchymal stem cells (BM-MSCs), which are the main cellular

components of the bone marrow (BM), have been deeply investigated in order to

clarify their significant contributions to heamatopoietic stem cells (HSCs) and

organ transplantation because of their intrinsic ability to differentiate into

functional cell types and immunsuppressive properties. BM-MSCs provide a

supportive microenvironment for maintanance of healthy heamatopoiesis. Their

contributions in the prevention of bone marrow rejection by supporting and

32

enhancing engraftment potential of newly developing hematopoiesis is very

important that raises the question what type of cellular interaction is available in

bone marrow microenvironment. The specific microenvironment in which HSCs

interact with MSCs is called as stem cell niche that is important for heamatopoietic

regeneration including erythropoiesis. BM-MSCs both provide the supportive

microenvironmental niche for hematopoietic stem cells (HSCs) and facilitate HSC

maintenance by secreting soluble factors and direct cell-to-cell contact.

Beta thalassemia is a genetic based hematological disease resulting from lack or

reduced synthesis of β-globin chains in hemoglobin because of partial or total

mutations in the genes of these chains. The defect in hemoglobin cause deep

anemic symptoms that leads to increased but non effective erythropoietic activity

in bone marrow that is called as ineffective erythropoiesis. How cell-to-cell

interactions between hematopoietic cells and BM-MSCs are effected during

genetic based beta-thalassemia major (β-TM) disease condition have not been

investigated yet. Within this context, in the first part of the study we aimed to

investigate the molecular changes of BM-MSCs in β-TM disease pathology by

FTIR spectroscopy and microspectroscopy. We hypothesized that hematopoietic

defect in β-TM may induce changes in morphological, proliferative, differentiative

and molecular properties of BM-MSCs as a result of cellular interactions between

defective HSCs and healthy BM-MSCs.

In the second part of the study we aimed to investigate the molecular level effects

of donor age on BM-MSCs properties by means of FTIR spectroscopy and

microspectroscopy. A complete characterization of the cellular, biochemical, and

molecular interactions of MSCs with their niche components is needed to

understand how these cells can be optimally regulated in vitro. Therefore;

understanding the effect of donor age on efficiency of tissue homeostasis, disease

33

recovery and the success of therapeutic application has to be answered. In this

context, we hyphothesized that infrared spectroscopy can be used as a new, non-

destructive research method that enables real-time chemical monitoring, high-

quality data collection with less experimental complexity to identify novel

molecular marker(s) that reflects the stem cell aging.

34

CHAPTER 2

MATERIALS and METHODS

2.1. Materials

2.1.1. Chemicals

The list of used and their suppliers are given in Appendix A.

2.1.2. Mesenchymal Stem Cells and Hematopoietic Stem Cells

Human bone marrow aspirates (3-5 ml) which were obtained from posterior iliac

crest of healthy bone marrow donors and patients with thalassemia major were

used as a source of BM-MSCs and HSCs. All samples were taken after signing of

informed consent that were prepared according to procedures approved by the

ethics commitee of the Hacettepe Univesity Childrens Hospital, BMT Unit

Ankara, Turkey.

2.1.2.1. Sampling Groups

2.1.2.1.1. Study 1

Human BM-MSCs were isolated from bone marrow samples of β-TM patients

before and after their BMT therapy. The aged matched healthy mesenchymal stem

35

cells were used as a control. The groups that were used to obtain BM-MSCs

during this part of the study were ordered in below.

Control Group (n=5): Aged matched healthy bone marrow donors.

Pre-Transplant Group (n=5): Patients before BMT therapy.

Post-Transplant Group (n=5): Same patients after BMT therapy.

2.1.2.1.2. Study 2

Human BM-MSCs of healthy donors from different ages were used in the second

part of the thesis study. The BM-MSCs were grouped according to human life

cycle and development stages. The groups that were used to obtain BM-MSCs

during this part of the study were ordered in below.

Infants: Ages were between 0-3 (n=5)

Children: Ages were between >3-12 (n=5)

Adolescents: Ages were between >12-19 (n=5)

Early Adults: Ages were between >19-35 (n=5)

Mid-Adults: Ages were between >35-50 (n=5)

2.2. Methods

2.2.1. Cell Culture Experiments

2.2.1.1. Isolation and Cultivation of Mesencyhmal Stem Cells from Human

Bone Marrow Samples

Bone marrow aspirates (3-5 ml) were diluted in an equal volume of 0,9%

phosphate buffer solution (PBS) (Sigma, USA). They were subjected to

36

fractionation on a density gradient solution Ficoll (1.077 g/l; Biochrom AG,

Berlin, Germany) to obtain mononuclear cells (MNCs). MNCs were then washed

twice with PBS and cultivated in complete medium contaning Dulbeco’s Modified

Eagle Medium-Low Glucose (DMEM-LG; Biochrom AG, Berlin, Germany), 10%

(vol/vol) Fetal Bovine Serum (FBS; Biochrom AG, Berlin, Germany), 1%

(vol/vol) L-glutamine (0.584 g/l; Biochrom AG, Berlin, Germany), 1% (vol/vol)

penicillin (100 units/ml) and streptomycin (100 g/ml) (Biochrom AG, Berlin,

Germany), 0,1% (vol/vol) Leukemia Inhibitory Factor (LIF) (0,5 µg/ml in 1%

BSA solution; Invitrogen) at 37°C in a 5% CO2 environment to obtain primary

BM-MSCs culture. After 24 hours non-adherent mononuclear cells were discarded

and adherent primary MSCs called as passage 0 MSCs, were expanded by

replacing culture medium twice a week. After the cells reached 80% confluency in

2 weeks, they were detached with 3ml 0.25% Trypsin + 1mM EDTA in PBS for

10 mins. The trypsinization was blocked with 10% FBS supplemented cmplete

medium and then the cells were washed with PBS once and harvested with

centrifugation at 1500 rpm for 5 minutes by using Eppendorf International 5810

centrifuge. 3x105 viable cells were plated per T75 culture flask for following

passages. The cells were counted by Thoma Lam after mixing with trypan blue by

considering their viability. All detailed investigations in scope thesis study were

perfomed by using passage 3 BM-MSCs.

2.2.1.2. Freezing and Storage of Bone Marrow Mesenchymal Stem Cells

The cells were stored at -196°C in liquid nitrogen cooled special tank to use during

thesis study. The cells were firstly suspended in freezing medium containing 10%

(vol/vol) DiMethylSulfoxide (DMSO, Applichem, Germany) suplemented with

20% (vol/vol) FBS and 70% (vol/vol) DMEM-LG on ice. Then the cell suspension

was aliquoted into cryovials (Greiner Bio-One) as 1x106 MSCs/ 1 ml/ tube on ice.

37

Cryovials were placed in a Mr. Frosty freezing container (Nalgene Labware,

Rochester, NY, http://www.nalgenunc.com) for 24 hours at -80oC. After Mr.

Frosty was stored at -80°C overnight, cryotubes were transferred to -196°C liquid

nitrogen tank for long term preservation.

2.2.1.3. Characterization of Bone Marrow Mesenchymal Stem Cells

2.2.1.3.1. Morphological Assessment

BM-MSCs was evaluated in terms of their adherence onto the plastic surface of

culture flask and fibroblast like morphology under inverted light microscopy.

2.2.1.3.2. Differentiation Experiments

Healthy and thalassemic BM-MSCs were induced for osteogenic and adipogenic

differentiation by cultivating them into the special differentiation mediums during

21 days.

2.2.1.3.2.1. Adipogenic Differentiation

After harvesting trypsinized BM-MSC (at P2) by centrifugation at 1500 rpm for 5

mins by using Eppendorf International 5810 centrifuge, the trypsinization was

blocked with 10% FBS supplemented complete medium and then cells were

washed with PBS once and harvested with centrifugation by using Eppendorf

International 5810 centrifuge at 1500 rpm for 5 minutes into cells. The washed

cells were seeded in 6-well plates at a density of 25x103 cells/well. The cells were

expanded in complete medium until 90-100% conflueny. Then medium was

removed and replaced with adipogenic induction medium including DMEM-LG

(Biological Industries, Israil), 10% of Fetal Bovine Serum (FBS) (Gibco, USA),

38

1µM dexamethasone (Sigma, USA), 60 µM indomethacine (Sigma, USA), 500 µM

IBMX (Sigma, USA) and 5 µg/ml insulin (Sigma, USA). The induction medium

of wells was replenished every 3 days and also adipogenesis was followed by

microscopic investigation during 21 days period. Meanwhile, the cells in control

well were cultured for 21 days in low glucose DMEM with 10% FBS. At the end

of differentiation period cells were stained with Oil Red O (Sigma,USA) to

visualize adipogenic differentiation.

2.2.1.3.2.1.1. Oil Red O Staining for Adipogenic Differentiation Assessment

At specified time points, adipogenic induction media was aspirated and the wells

were washed with PBS buffer. The fixation of cells was done in 10% formol

(Sigma, USA) for 20 mins at RT. After fixation, cells in each well were stained

with 500 µl Oil Red O solution (Sigma, USA) by incubating at RT for 10 mins. At

the end of 10 mins, the Oil Red O Solution was aspirated and cells were rinsed

gently with for dH2O two times. For picture capturing (Olympus, Japan), 1-2 ml

dH2O was added into the wells. Then cells were rinsed and incubated for 1 hour

with %2 igepal/isopropanol (v/v) (Sigma-Aldrich, USA; DOP Organik Kimya

Sanayi, Turkey) for quantitative analysis of lipid droplets.

2.2.1.3.2.2. Osteogenic Differentiation

After harvesting trypsinized passage 2 BM-MSC by centrifugation at 1500 rpm

(Eppendorf International 5810) for 5 mins, cells were washed with PBS and then

seeded in 6-well plates at a density of 12.5x103 cells/well. Cells were expanded in

complete medium until 60-70% conflueny. Then medium was removed and

replaced with osteogenic induction medium consisting DMEM-LG (Biological

Industries, Israil), 10% of Fetal Bovine Serum (FBS) (Gibco, USA), 100 nM

dexamethasone (Sigma, USA), 10 mM beta glycerophosphate (Sigma, USA) and

39

0.2 mM ascorbic acid (Sigma, USA). Meanwhile, the cells in control wells were

cultured for 21 days in low glucose DMEM with 10% FBS. The induction medium

of wells was replenished every 3 days and also osteogenesis was followed by

microscopic investigation during 21 days period. At the end of differentiation

period cells were stained with Alizerin Red Stain (Sigma,USA) to visualize

osteogenic differentiation.

2.2.1.3.2.2.1. Alizerin Red Staining for Osteogenic Differentiation Assessment

At specified time points, osteogenic induction media was aspirated and the wells

were gently washed with PBS buffer. The fixation of cells was done in 10%

formol (Sigma, USA) for 20 mins at RT. After washing with dH2O, Alizarin Red

solution (Sigma,USA) was left at room temperature in wells for 10 minutes. At the

end of 10 mins, the stain was aspirated and cells were gently washed with dH2O

for 3 times to remove any nonspecific staining. Then 1-2 ml distilled water was

added to each well for imaging of stained area by microscopically (Olympus,

Japan).

2.2.1.3.3. Immunophenotyping of Bone Marrow Mesenchymal Stem Cells by

Flow Cytometry

2.2.1.3.3.1. Cell Surface Marker Staining

The analysis of cell surface markers were studied by passage 3 BM-MSCs. The

cells in T75 flasks were washed with PBS buffer for once and then trypsinized at

37°C for 10 mins. The trypsinization was blocked with 10% FBS supplemented

with complete medium and then washed with PBS once and harvested with

centrifugation at 1500 rpm (Eppendorf International 5810) for 5 minutes into the

falcon tubes.

40

Previously, trypsinized passage 3 BM-MSCs were separated into different flow

cytometry tubes in 2ml PBS buffer at a density of 2x105 cells/tube for specific cell

surface marker staining. After centrifugation at 1500 rpm for 5 mins supernatant

was removed and cell pellet was distributed by finger tapping. 100 µl PBS-BSA-

Na Azide and CD34 (BD Biosciences, USA), CD45 (BD Biosciences, USA),

CD73 (BD Biosciences, USA), CD90 (BD Biosciences, USA), CD105 (E-

Bioscience, USA), CD133 (E-Bioscience), antibodies were added homogenized

cell pellet and then tubes were incubated +4°C for 30 min by covering thinfoil. At

the end of 30 mins incubation in dark, cells were washed twice with 2 ml PBS-

BSA-Na Azide and centrifuged at 1500 rpm (Eppendorf International 5810) for 10

minutes. Finally, cells were resuspended in 200 µl PBS-BSA-Na Azide in FACS

tubes and analyzed in FACS Aria (Becton, Dickinson Biosciences, USA).

2.2.1.3.3.2. Flow Cytometry Analysis

The analysis of cells was done according to 10.000 event count with the FACS

Aria (Beckon Dickinson Biosciences, USA). The channel choice, gating and

compensation adjustments were done related to sample and staining properties.The

analysis of acquired data was carried out using BD FACSDiva Software v6.1.2

(Becton, Dickinson Biosciences, USA).

2.2.1.4. MTT (Thiazolyl Blue Tetrazolium Bromide) Proliferation Assay

Passage 2 BM-MSCs were trypsinized and the trypsinization was blocked with 1

complete medium. After the cells were washed with PBS once and harvested with

centrifugation at 1500 rpm (Eppendorf International 5810) for 5 minutes into

falcon tubes, they were seeded in a 96-well plates at a density of 1x104 cells/well

in 200 µl complete medium. Cultured cells were expanded in 5% CO2 incubator at

37ºC to obtain passage 3 BM-MSCs which were used in MTT assay. One set of

41

wells with MTT and complete medium without cells were used as a blank control.

20 µl MTT (5mg/ml in PBS) (Thiazolyl Blue Tetrazolium Bromide, Sigma-

Aldrich,USA) solution was added to each well at day 1, 3, 5, 7, 9 and 11 of

culturing. After addition of MTT 96-well plate was covered with thinfoil and

incubated for 4 hours at 37ºC in 5% CO2 incubator in dark. After incubation period

was completed in dark side, the black formazan crystals were observed by

inverted ligth microscope at the bottom of the wells. Once the incubation time was

ceased, 100 µl sodium dodesyl sulphate (SDS) (Sigma-Aldrich,USA) was put into

each well and then incubated at room temperature for 24 hours by covering the

plate thinfoil. SDS which is defined as MTT solvent dissolves formazan cystals,

producing a purple solution. At the end of incubation time, the absorbance of each

well was measured at 620 nm using ELISA reader (Tecan Systems Inc., San Jose,

CA, USA).

2.2.1.5. Determination of Eythropoietin (EPO) and Growth Differentiation

Factor 15 (GDF 15) Levels in Bone Marrow Plasma Samples

Bone marrow samples of thalassemic patients and healthy donors were collected

into heparin anticoagulant containing tubes. The tubes were centrifuges at 2500

rpm (Eppendorf International 5810) for 15 minutes to obtain BM plasma samples.

Quantification of EPO and GDF15 levels of BM plasma samples was performed

by ELISA assays for human EPO (Quantikine IVD, R&D Systems, Minneapolis,

USA) and for human GDF 15 (Quantikine IVD, R&D Systems, Minneapolis,

USA) according to the instruction manual of manufacturer’s. While BM plasma

samples were used immediately in ELISA assays, remaining plasma samples were

stored at -20 ºC by aliquoting.

42

2.2.1.6. Analysis of Chimerism by Short Tandem Repeat Polymerase Chain

Reaction (STR-PCR)

Genomic DNAs were extracted from recipient and donor BM-MSCs samples

using MagNA Pure Systems (Roche) according to the manufacturer’s

recommendation. AmpFlSTR Identifiler amplification kit (Applied Biosystems)

was used to perform STR-PCR. The kit amplifies 15 loci (CSF1P0, D7S820,

D8S1179, D21S11, D2S1338, D3S1358, D13S317, D16S539, TH01, D1S51,

D19S433, TPOX, vWA, D5S818, FGA and Amelogenin in a single tube and

provides loci consistent with major world-wide STR databasing standards. PCR

was performed using 1 ng of genomic DNA in a final reaction volume of 15 µl as

suggested by the manufacturer. The PCR cycle conditions were: 95°C for 11 min,

followed by 28 cycles with 94°C for 1 min, 59°C for 1 min and 72°C for 1 min.

The final elongation step was 60 min at 60°C. The PCR products were analyzed

with an ABI PRISM 310 DNA sequencer and GeneScan Analysis software

(Applied Biosystems) as described in the the instruction manual of

manufacturer’s. Percentage donor chimerism was assumed from the peak area

contributed by one heterozygous allele, visible distinct in the mixed profile, was

identical to that area contributing to a mix ture of donor and recipient. Chimerism

analysis was perfomed in DNA Analysis Laboratory of Hacettepe University

Faculity of Medicine Department of Pediatric Hematology as a procurement of

services.

43

2.2.2. Fourier Transform Infrared (FTIR) Spectroscopy and

Microspectroscopy Experiments

2.2.2.1. Attenuated Total Reflectance (ATR-FTIR) Spectroscopy Study

2.2.2.1.1. Sample Preparation

In ATR-FTIR spectroscopy measurements, 2x106 BM-MSCs at passage 3 were

used. MSCs cells harvested by 5 mins centrifugation at 1500 rpm (Eppendorf

International 5810) after 10 mins trypsin (0.25% Trypsin+1Mm EDTA) treatment

at 37°C in a 5% CO2 environment. Then cell pellet was washed twice with 1ml

0.9% PBS solution to remove all groving media. The cell pellet was re-suspended

in 10 µl 0.9% PBS buffer and then cell suspension was deposited on

Diamond/ZnSe (Di/ZnSe) crystal plate of the Universal ATR unit of the FTIR

spectrometer by rapidly evaporating using mild N2 flux during 30 mins to obtain a

homogenous film of entire cells on ATR crystal.

2.2.2.1.2. Data Acquisition and Spectroscopic Measurements

Infrared spectra were obtained by scanning the prepared homogenous BM-MSCs

film on Diamond/ZnSe (Di/ZnSe) crystal plate of the Universal ATR of Spectrum

100 FTIR spectrometer in the one-bounce ATR mode (Perkin-Elmer Inc.,

Norwalk, CT, USA). The spectra were recorded in the 4000-650 cm-1 region at

room temperature. A total of 100 scans were taken for each interferogram at 4 cm-1

resolution. The spectrum of atmospheric water vapor and carbondioxide

interference were recorded as background and then subtracted automatically using

the Spectrum One Software program. Figure 2.1 shows the infrared spectrum of

air. In order to prevent the contribution from the inorganic phosphate in PBS, 10

44

µl PBS buffer was first dried with nitrogen (N2) flux during 30 minutes and the

buffer spectrum was subtracted from the cell spectra. Figure 2.2 shows the infrared

spectra of the PBS buffer. Recording and analysis of the spectral data were

performed using the Spectrum One Software from Perkin Elmer.

Before the spectral analysis are performed, according to the requirements of

analysis technique, some preprocessing steps are applied to the spectral data sets to

make the spectra comparible. By these preprocessing approaches the number of

variables can either be reduced to prevent overfitting. Baseline correction, which is

4000 3600 3200 2800 2400 2000 1800 1600 1400 1200 1000 800 650

WAVENUMBER (cm-1)

Figure 2.1 Infrared spectrum of air.

ABSORBANCE

45

mainly used to get rid of a sloping and curving baseline, is a wavelength-

dependent intercept and unique for each sample spectrum (Franke, 2006). The

detailed data analysis and accurate determination of the variations in band area

values original base-line corrected spectrum was considered, while the band

positions (frequency values) were measured according to the center of weight of

the peaks from raw spectral data. All these mentioned quantitative analysis were

performed on non-normalized but pre-processed average spectra. However, by the

purpose of visual presentation of the differences, the average spectra of sampling

groups were normalized with respect to the specific bands and information about

the intensity of the spectrum is completely eliminated (Kramer, 1998).

4000 3600 3200 2800 2400 2000 1800 1600 1400 1200 1000 800 650

WAVENUMBER (cm-1)

Figure 2.2 The ATR FTIR spectrum of PBS buffer solution.

ABSORBANCE

46

2.2.2.1.3. Statistical Analysis

The results of spectral measurements were expressed as “mean ± standard error”

values. The spectra were analyzed by using different spectral parameters like band

frequencies, band widths and band areas. As first, the data were evaluated by

normality test to decide whether the parametric or non-parametric statistical test to

be used. Since the data showed normal distribution, they were compared to each

other by using One Way Anova and Tukey Multiple Comparison Test by

considering their statistical significances in terms of p<0.05, p<0.01, p<0.001.

2.2.2.1.4. Cluster Analysis

It was applied to find out spectral relationships among sampling groups that were

investigated in the study. The first derivativative, vector normalized spectra were

used in the cluster analysis by using OPUS 5.5 software (Bruker Optic, GmbH) in

order to distinguish control and thalassemic MSCs, and also to distinguish MSCs

belonging to different age groups. Cluster analysis is separated the spectra of

samples according to their spectral similarities and differences. The result of the

analysis are represented in the form a dendrogram. The change in variances

between the spectra of samples is represented by heterogeneity values. Higher

heterogeneity in between the clusters demonstrates higher differences among

analyzed groups. Pearson’s correlation coefficients were used to measure the

distances between the pairs of spectra. Ward’s algorithm was used to construct

dendograms for hierarchical clustering. The details of the calculation and

algorithm can be found in Severcan et al., 2010.

47

2.2.2.2. FTIR Microspectroscopic Study

2.2.2.2.1. Slide Preparation

2.2.2.2.1.1. Deposition and Fixatition of BM-MSCs on Low-e Microscope

Slides

Passage 3 BM-MSCs were trypsinized and after the tryspsin was blocked with

10% FBS collected with centrifugation at 1500 rpm (Eppendorf International

5810) for 5 mins, the cell washed with PBS once and then the two final washings

were performed with serum physiologic solution to remove salt crystals. The cell

pellet was dissolved in 1mL of culture medium and BM-MSCs were counted with

thoma lam by using trypan blue. 25.000 MSCs were placed on silver (Ag/SnO2)

coated low-e microscope slides and they were grown on at 37ºC in a 5% CO2

environment by overnigth cultivation. At the end of cultivation time, MSCs on

low-e microscope slide were fixed by 10% formalin for 10 minutes. In order to

remove excess formalin, slides were washed with serum physiologic solution and

then they were kept in dry environment to evaporate excess solution at room

temperature for at least 1 hour.

Fixation is a major issue after cells are deposited onto microscope slides. Air

drying is a mild form of fixation and for further fixation some chemicals such as

ethonol, methanol, acetone and formalin are used. Ethanol and methanol cause

minor spectral changes because of removal of phospholipids and minor changes

are observered in the main protein bands amide I and amide II (Romeo et al.,

2008). Acetone fixation decreases cell volume, breaks hydrogen bonds and causes

coagulation of water-soluble proteins and the destruction of cellular organelles

(Hasting et al., 2008). Therefore, buffered formalin that preserves lipids and has

little impact on carbohydrates is generally used for fixation of cells that will be

48

used in IR microscopy. 10% buffered solution of formaldehyde, is called as

formalin, preserves protein secondary structure of cells and it does not harm the

spectra of cells (Romeo et al., 2006). After fixation, cells have to be washed with

deionized water or physiological saline solution (0.9 % NaCl) in order to prevent

hemolysis. Then they have to be dried very quickly under a stream of dry and

compressed air. The attachement of cells to the slide is so strong that they can be

fixed onto the slide by chemically without dislodging them (Romeo et al., 2006;

Romeo et al., 2008).

The low-e MirrIR slides are coated with Ag/SnO2 layer which provide reflectance

property of slides. Infrared beam is reflected by Ag/SnO2 layer through a thin

sample. Since the low-e slides are transparent in the visible region, before IR

A B

Figure 2.3 Inverted ligth microscopy images of BM-MSCs that were directly grown on silver coated low-e FTIR microscopy slides. A) Before formalin fixation. B) After formalin fixation.

49

imaging of cells samples can be examined by light microscope as it can be seen

from Figure 2.3.

2.2.2.2.2. Collection of Visible Images and Spectral Maps

Perkin Elmer FTIR microscope coupled with Perkin Elmer Spotlight 400 software

was used to map MSCs samples on slides. The microscope is equipped with a

liquid nitrogen cooled MCT detector and a CCD camera to provide an optical

image of the area under interrogation. An aperture size of 6.25µm X 6.25µm was

used to obtain spectra from confluent monolayers. IR image maps were collected

in the reflection mode through the spectral range between 4000-700 cm-1 with a 4

cm-1 resolution and 32 scan numbers. Background spectra were collected from a

separate piece of blank MirrIR low-e slide. At least 3 spectra were acquired from

each sample.

2.2.2.2.2.1. Selection of Spectral Images and Preprocessing of Spectral Data

ISys software (Spectral Dimensions, Olney, MD, USA) was used to analyze the

conventional FTIR microspectroscopic data. ISys programme uses image files

with the .spf extention, however; Perkin Elmer FTIR microscope coupled with

Perkin Elmer Spotlight 400 software provides image files with .fsm extention.

Therefore, at the beginnig of image data analysis with ISys software, the .fsm

extended files were translated to .spf extended ones. Whole baseline correction

were performed between 3800-800 cm-1 region. Then spectral masking was

applied for analysis by using ISys software to get rid of the contributions from the

surface around the cellular regions by marking the cells. The chemical maps were

constructed for each group by taking area of specifically selected spectral bands

arisen from lipids, proteins and nucleic acids. The integrated spectral regions for

50

the infrared bands that were used to determine distribution of functional groups

were presented in Table 2.1.

Table 2.1 The integrated spectral regions

Infrared Band Integrated Spectral Range (cm-1)

CH2 antisymmetric stretching 2944-2880

CH2 symmetric stretching 2864-2862

Amide I 1712-1534

Amide II 1534-1480

PO2- antisymmetric stretching 1272-1184

51

CHAPTER 3

RESULTS

Bone marrow mesenchymal stem cells (BM-MSCs) are found in BM

microenvironment with other cells like hematopoietic stem cells as a main cellular

supportive component. Therefore, prior to experiments BM-MSCs have to be

isolated from bone marrow samples and then they have to be characterized. BM-

MSCs were characterized by their adherence to plastic surface of culture flask and

their fibroblast like morphology under inverted light microscope according to the

rules of ISCT (International Society for Cellular Therapy) (Horwitz et.al., 2005;

Dominici et.al., 2006). These cells have to be evaluated for their expression of

CD73, CD90 and CD105 surface antigens and their capacity to differentiate into at

least osteoblasts and adipocytes by standard differentiation inducing media

(Dominici et.al., 2006) in order to be defined as MSCs. BM-MSCs that were used

in the thesis study were characterized first in terms of their morphological,

immunophenotypical and differentiation properties and then used in other

experimental parts of the study.

3.1. Harvesting of Mesenchymal Stem Cells from Bone Marrow Samples by

Culturing

As first, bone marrow MNCs were isolated from bone marrow aspirates by ficoll

extraction method as stated in section 2.2.1.1. Then, MNCs were seeded in plastic

culture flasks to obtain MSCs. At the first day of culturing of MNCs,

hematopoietic progenitor cells and erythrocytes were observed as unattached

52

bright cells in flask. Culture media was aspirated and replenished with fresh media

during two weeks to remove these concomitant cell types. While these

contaminating cells were eliminated with the media replenishment, BM-MSCs

were obtained by their plastic adherence property. These BM-MSCs were called as

passage 0 (P0) cells (Figure 3.1).

A B

C D

Day 1 Day 3

Day 14 Day 7

Figure 3.1 Photomicrograph of healthy BM-MNCs in culture flask during their expansion phases to obtain P0 MSCs. A) MNCs after 24 hours, B) Newly formed fibroblast like MSCs around erythropoietic colony, C) Fibroblast like MSCs and brigth hematopoietic cells, D) Confluent MSCs colony.(Mag = 10X)

53

Further passaging was performed to obtain pure P3 BM-MSCs that were used in

other experiments during the thesis study. In Figure 3.2, P1, P2 and P3 (passage

number will be stated as P1, P2, e.g.) BM-MSCs populations could be observed.

As can be seen from the Figure 3.2, while shiny hematopoietic cells were available

in P1, they disappeared during proceeding passages.

Figure 3.2 Healthy BM-MSCs at different passages. A) P1 MSCs with several round and shiny hematopoietic cells, B) P2 MSCs, C) P3 MSCs. (Mag = 10X)

C

A B

54

3.2. Characterization of Human Bone Marrow Mesenchymal Stem Cells

Bone marrow mesenchymal stem cells from healthy and thalassemic bone marrow

samples were isolated and characterized as mentioned in sections 2.2.1.1 and

2.2.1.3. After BM-MSCs were isolated by their adherence to plastic surface of

culture flask and their morphological characterization was performed by inverted

light microscopy. They were also analyzed in terms of their expression of BM-

MSCs’s surface markers by flow cytometry.

3.2.1. Flow Cytometry Analysis of CD Marker Expression Profile of Bone

Marrow Mesenchymal Stem Cells

In the late passages, the genes that are involved in cell cycle, DNA replication and

DNA repair are significantly down-regulated (Wagner et al., 2010). Passaging

over and over can affect stem cell like potential of MSCs that they can loose their

stemness properties (Yu et al., 2010), while early passages contain contaminating

cells which decrease purity of MSC population. Therefore, both in the first and the

second part of the thesis BM-MSCs were used in P3.

Passage 3 BM-MSCs, which were used in the present study, were evaluated for

their expression of MSCs surface antigens CD105, CD73, CD90, CD34, CD45.

Both thalassemic and healthy BM-MSCs were positive for CD105, CD73 and

CD90 antigens in ≥95%, while they showed lack of expression for heamatopoietic

markers CD45, CD34, as stated in the definitions of ISCT for MSCs (Dominici et

al., 2006). There was no difference in the levels of expressions of BM-MSCs

specific surface antigens between P3 thalassemic and their healthy control BM-

MSCs (Figures 3.3, 3.4 and 3.5).

55

In the scope of second part of the thesis, P3 BM-MSCs obtained from different age

donors showed same expression profile for surface antigens CD105, CD73, CD90,

CD34, CD45. They expressed CD105, CD73 and CD90, while they did not show

any expression for CD34 and CD45.

A B

Figure 3.3 The FSC/SSC parameters of passage 3 BM-MSCs A) Healthy BM-MSCs; B) Thalassemic BM-MSCs.

99% 99,4% 99,5%

Figure 3.4 Surface antigen profile of healthy BM-MSCs at passage 3.

56

3.2.2. Differentiation Analysis of Bone Marrow Mesenchymal Stem Cells

Healthy and thalassemic BM-MSCs, which were cultivated till P3 in six well

culture dishes, were investigated in terms of their adipogenic and osteogenic

differentiation potentials.

3.2.2.1. Adipogenic Differentiation Analysis

Mesenchymal stem cells can be differentiated into different lineages by using

selective induction media supplemented with specific compounds at specific

concentrations.

In the first part of the thesis study, adipogenic differentiation potentials of P3

thalassemic BM-MSCs before and after bone marrow transplantation therapy

(BMT) and their healthy controls were examined by using specific adipogenic

induction media. Adipocyte conversion of BM-MSCs by incubating with selective

media takes 21 days. By the 6th day of an induction, shiny lipid droplets started to

be observed in the BM-MSCs. Throughout the induction period, the lipid droplets

Figure 3.5 Surface antigen profile of thalassemic BM-MSCs at passage 3.

99,5% 99,5% 99,3%

57

became larger and increased in number. At the end of induction period, they filled

the cytoplasm and Oil Red O staining were perfomed to evaluate adipocyte

differentiation. Morphological assessment of induced cells was performed under

inverted light microscope. Figure 3.6 shows adipogenic differentiation results of

thalassemic BM-MSCs before and after BMT therapy and healthy control BM-

MSCs. There was no morphological difference for the adipogenic differentiation

of healthy and thalassemic BM-MSCs. In the second part of the study adipogenic

differentiation potentials of healthy BM-MSCs that were obtained from volunteer

BM donors in different ages were compared. The results showed that BM-MSCs

of younger and older donor groups differentiated into adipocytes (Figure 3.7).

Figure 3.6 Oil Red O staining of thalassemic and healthy control BM-MSCs at the end of 21 days. A) Healthy BM-MSCs, B) Thalassemic MSCs before transplantation, C) Thalassemic MSCs after transplantation. (Mag = 20X)

A B C

58

3.2.2.2. Osteogenic Differentiation Analysis

In the first and the second part of the thesis study, BM-MSCs were induced by

using specific induction media for osteogenic differentiation during 21 days. By

the 7th day of induction, fibroblast like morphology of BM-MSCs started to change

and they became larger, dark-colored calcium deposition was observed in cells. As

the induction period continued, the number of amorphous calcium deposition

increased and filled up the cell cytoplasm. At the end of induction period, calcium

deposition in differentiated cells were observed by Alizerin Red staining as black

crystals under inverted light microscope as an indicator of osteogenic

Figure 3.7 Oil Red O staining of healthy P3 BM-MSCs at the end of 21 days A) Infants MSCs, B) children MSCs, C) adolescents MSCs, D) early adults MSCs, E) mid adults MSCs. (Mag = 20X)

B C

D E

A

59

differentiation. The osteogenic differentiation results of thalassemic BM-MSCs

before and after BMT therapy with their healthy control BM-MSCs are shown in

Figure 3.8. The osteogenic differentiation of BM-MSCs that was obtained from

different aged healthy donors is presented in Figure 3.9.

Figure 3.8 Alizerin Red staining of thalassemic and healthy control BM-MSCs at the end of 21 days A) Healthy MSCs, B) Thalassemic MSCs before transplantation, C) Thalassemic MSCs after transplantation. (Mag = 20X)

A B C

60

3.3. Results of Chimerism Analysis Following Bone Marrow Transplantation

In the present study, chimerism analysis was performed by amplifying 15 STR loci

in genomic DNA to determine whether BM-MSCs were of recipient or donor

origin after bone marrow transplantation (BMT) therapy. STR-PCR is based on the

amplification of tetranucleotide STR loci by PCR. Post-transplant DNAs of BM-

MSCs of our all 5 patients were obtained between +25 and +35 days after

transplantation and they were used in chimerism test by comparing pre-transplant

DNA of patients and DNA of donors. Our chimerism results showed that after

BMT bone marrow MSCs were of patient origin while while complete donor type

Figure 3.9 Alizarin Red staining of healthy P3 BM-MSCs at the end of 21 days. A) Infants MSCs, B) children MSCs, C) adolescents MSCs, D) early adults MSCs, E) mid adults MSCs. (Mag = 20X)

A B C

D E

61

hematopoietic engraftment was present in all patients. The results of chimerism

analysis revealed that BM-MSCs were of 100% patient origin while there were

between 95% and 99% donor type HSCs engraftment in their bone marrows.

3.4. FTIR Spectroscopy Results

The thesis study was aimed to investigate molecular level differences or

similarities in human BM-MSCs during human aging periods and thalassemia

disease states. The FTIR spectrum of BM-MSCs represents many different

functional groups belonging to many different macromolecules.

Fourier-transform infrared (FT-IR) spectroscopic approach is very convenient to

obtain quantitative and structural information about biological samples. The

specific groups of atoms in the system are defined by specific infrared absorption

bands that are assigned to specific vibrational modes of particular functional

groups in molecule (Steele, 1971).

Attenuated Total Reflection (ATR) mode of FTIR spectroscopy does not require

detailed sample preparation procedure (Kazarian et al., 2006; Perkin Elmer Life

and Analytical Sciences, 2005). ATR-FTIR is based on the total reflection

phenomenon. When the radiation beam passes through an ATR crystal, it is

internally reflected that causes creation of evanescent wave protruding only a few

micrometers beyond the surface of ATR crystal. The distance that the wave

extends from the crystal surface is about 1,66 µm for ZnSe diamond ATR crystal.

The radiation that penetrates a fraction of a wavelength beyond the surface of the

crystal enters the sample that is placed on its surface (Perkin Elmer Life and

Analytical Sciences, 2005). A solid sample can be directly placed on ATR crystal

by applying a pressure to obtain best contact for realible FTIR spectra, however;

cells are deposited onto crystal by evaporating the cell suspension buffer to form

62

cell film. When the infrared beam reflected through the ATR crystal, the sample

absorbs a part of the radiation as a result of an interaction and the sample interface

produces an absorbance spectrum (Kazarian et al., 2006; Gaigneaux et al., 2006).

3.4.1. General FTIR Spectrum and Band Assignments of Thalassemic and

Healthy Control Bone Marrow Mesenchymal Stem Cells

Figure 3.10 shows the averaged representative infrared spectrum of thalassemic

and healthy control BM-MSCs in the 3800-800 cm-1 region. The wavenumber

(frequency) values of the bands at peak positions were used to assign the bands.

The main bands are labelled with numbers in the figure and specific assignments

of these spectral bands for BM-MSCs are listed in Table 3.1.

63

64

Table 3.1 General band assignment of human bone marrow mesenchymal stem cells.

Peak No

Wavenumber (cm-1)

Definition of the sprectral assignments

1 3330 Amide A: N-H and O-H stretching vibrations of polysaccharides, proteins

2 3065 Amide B: N-H vibrations of proteins

3 3015 Olefinic =CH stretching: unsaturated lipids, cholesterol esters

4 2957 CH3 antisymmetric stretching: lipids, protein side chains, wih some contribution from carbohydrates and nucleic acids

5 2924 CH2 antisymmetric stretching: mainly lipids, with the little contribution from proteins, carbohydrates, nucleic acids

6 2873 CH3 symmetric stretching: protein side chains, lipids, with some contribution from carbohydrates and nucleic acids

7 2852 CH2 symmetric stretching: mainly lipids, with the little contribution from proteins, carbohydrates, nucleic acids

8 1740 C=O stretching vibrations of triglycerides, cholesterol esters 9 1639 Amide I: C=O stretching vibrations of proteins

10 1545 Amide II: N-H bending and C-N stretching vibrations of

11 1453 CH2 bending vibrations of lipids 12 1402 COO- symmetric stretching: fatty acid side chains 13 1310 Peptide side chain vibrations

14 1234 PO-

2 antisymmetric stretching: fully hydrogen bonded: mainly nucleic acids with the little contribution from phospholipids

15 1152 CO-O-C antisymmetric strectching vibraitions of glycogen and nucleic acid ribose

16 1080 PO-

2 symmetric stretching: nucleic acids and phospholipids; C-O stretching: glycogen,polysaccharides, glycolipids

17 1045 CO stretching vibrations of carbohydrates, glycogen; deoxyribose/ribose of nucleic acids

18 1025 Mainly from glycogen 19 925 Sugar vibrations in backbone of DNA-Z form 20 855 Vibrations in N-type sugars in nucleic acid backbone

65

3.4.2. Comparison of Spectra of Thalassemic and Healthy Control Bone

Marrow Mesenchymal Stem Cells

In the first part of the thesis study, the differences in the structure and the function

of macromolecular components of healthy control BM-MSCs and thalassemic

BM-MSCs before and after BMT therapy were investigated by FTIR spectroscopy

and microspectroscopy. FTIR spectra of all samples were collected in 4000-650

cm-1 frequency region. A detailed spectral analysis was performed in two separate

regions, namely 3050-2800 cm-1, 1800-800 cm-1 (Figure 3.11 and Figure 3.12). As

seen from these figures, thalassemic and healthy control BM-MSCs spectra

substantially differ in band positions, band heights and band widths. The details of

these differences between thalassemic and control BM-MSCs were discussed in

Chapter 4 more specifically.

66

67

68

3.4.2.1. General Information about Numerical Comparisons of the Bands of

Thalassemic and Healthy Control Bone Marrow Mesenchymal Stem Cells

The spectrum of each sample was analyzed using Spectrum 100 Software by

considering different spectral parameters such as band frequencies, band widths

and band areas. The shift in the wavenumber (frequency) value of the spectral

band at peak position gives information about the structure/conformation and

intermolecular interactions (Jackson et al., 1997; 1999; Toyran et al., 2003), while

the area under the bands reflects the concentration of the related molecules

(Freifelder, 1982; Toyran and Severcan, 2003; Toyran et al., 2004). The band area

and band wavenumber values were expressed in terms of “means and standard

errors”. The baseline-corrected average spectra of each sample group were used to

perform accurate measurements of the spectral parameters. However, all spectra

represented in the figures were normalized with respect to the amide A band

centered at around 3330 cm-1 for illustrative purposes. Then the data were

evaluated by normality test in order to decide whether the parametric or non-

parametric statistical test to be used for an evaluation of statistical significancy.

Since in the present study, the data showed normal distribution; spectral

measurements were compared to each other by using One Way Anova and Tukey

Multiple Comparison Post Test. Statistical significances were conveyed in terms

of p<0.05, p<0.01, p<0.001. The changes in wavenumber and band area values are

given in Table 3.2 and in Table 3.3, respectively.

69

3.4.2.2. Detailed Spectral Analysis of Thalassemic and Healthy Control Bone

Marrow Mesenchymal Stem Cells

3.4.2.2.1. Comparison of Thalassemic and Healthy Control Bone Marrow

Mesenchymal Stem Cells in the 3050-2800 cm-1 region

The deconvolved and normalized averaged representative infrared spectra of

thalassemic and control BM-MSCs in the 3050-2800 cm-1 region are shown in

Figure 3.11. The spectra were normalized with respect to the amide A band

located at around 3360 cm-1. The 3050-2800 cm-1 region contains some important

bands. The band centered at 3015 cm-1 attributes C-H stretching mode vibrations

of the H-C=C-H groups. This olefinic C-H stretching band is used to determine the

level of unsaturation of phospholipid acyl chains (Takahaski et al., 1991; Melin et

al., 2000; Liu et al., 2002; Severcan et al., 2005). As given in Table 3.3, there was

a significant increase in the area of this band in pre-transplant group BM-MSCs

(0.658±0.02) (p<0.01) with respect to the value of healthy control BM-MSCs

(0.506±0.02). The area of this band was significantly lower in post-transplant

group (0.538±0.02) (p<0.01) when compared to pre-transplant group (0.658±0.02).

The other bands located at 2957 cm-1, 2924 cm-1, 2873 cm-1 and 2852 cm-1,

belongs to CH3 and CH2 antisymmetrical, and CH3 and CH2 symmetrical

vibrations, respectively (Melin et al., 2000; Chang and Tanaka, 2002; Cakmak et

al., 2003; Severcan et al., 2003; Cakmak et al., 2006). The CH3 antisymmetric, the

CH2 antisymmetric and the CH2 symmetric stretching bands originate mainly from

lipids, the CH3 symmetric stretching band originates mainly from proteins

(Mantsch, 1984; Severcan et al., 2000; Severcan et al., 2003; Cakmak et al.,

2006). As seen in Table 3.3, the area of CH3 antisymmetric, CH2 antisymmetric

and CH2 symmetric stretching bands significantly (p<0.05) increased in pre-

transplant thalassemic BM-MSCs with respect to the control ones. However, after

70

BMT therapy we observed tendency to decrease in the area of these bands

according to pre-transplant BM-MSCs.

The shifts in the wavenumber values of the CH3 and CH2 antisymmetric, CH2

symmetric stretching bands are related to the order/disorder states of membrane

lipids (Toyran et al., 2004; Umemura et al., 2000). The changes in the frequency

values of the band at 2957 cm-1 provides structural information about deep interior

part of the membrane (Mantsch, 1984; Severcan et al., 1997). The wavenumber of

this band tended to decrease both in pre (2957.194±0.173) and post-transplant

(2957.228±0.156) BM-MSCs with respect to the healthy controls BM-MSCs

(2957.428±0.124). The peak positions of CH2 antisymmetric and symmetric

stretching bands determine degree of conformational order/disorder of the

membrane structures and give information about the average trans/gauche

isomerization of membrane fatty acids (Mantsch, 1984; Severcan et al., 1997;

Bizeau et al., 2000). The reduction in CH2 antisymmetric stretching band

frequency was significant in pre-transplant group (2923.88±0.144) (p<0.05) when

compared with healthy control group (2924.68±0.342). The frequency of the CH2

symmetric stretching band shifted to a lower values for the pre- and post-transplant

groups according to the control group (Table 3.2).

Table 3.2 Changes in the wavenumber values of some infrared bands for the healthy control, pre and post-transplant BM-MSCs. The values were shown as ‘mean ± standard error’ for each group. The degree of significance was denoted as: *p<0.05 with respect to the healthy control group.

Healthy Control

(n=5) Pre-Transplant

(n=5) Post-Transplant

(n=5)

Wavenumber (cm-1) Band wavenumber 2957 2957.428±0.124 2957.194±0.173 2957.228±0.156 2924 2924.684±0.342 2923.88±0.144*↓ 2924.316±0.122 2852 2853.022±0.376 2852.514±0.034 2852.718±0.087

71

Table 3.3 Changes in the band area values of the infrared bands for control, pre and post transplant BM-MSCs. The values were shown as ‘mean ± standard error’ for each group. The degree of significance was denoted as *p<0.05, **p<0.01, ***p<0.001 according to the healthy control group and †p<0.05, ††p<0.01 according to the pre-transplant group.

Band Area

Band No

Band Wavenumber

(cm-1) Healthy Control

(n=5) Pre-Transplant

Group (n=5) Post-Transplant

Group (n=5)

3 3015 0.506±0.02 0.658±0.02 **↑ 0.538±0.02 ††↓

4 2957 1.522±0.097 1.958±0.074 *↑ 1.766±0.123

5 2924 2.510±0.09 3.172±0.118 *↑ 2.890±0.177

6 2873 0.334±0.01 0.424±0.016*↑ 0.38±0.026

7 2852 0.586 ±0.042 0.746±0.033 *↑ 0.654±0.045

8 1740 0.40±0.01 0.48±0.01 *↑ 0.41±0.02 †↓

9 1639 17.371±0.456 19.22±0.366 *↑ 18.71±0.577

10 1545 7.158±0.339 11.78±0.759 ***↑ 10.07±0.484 **↑

11 1453 1.584±0.108 2.606±0.124 ***↑ 2.382±0.189 **↑

12 1402 2.064±0.084 3.792±0.284 ***↑ 3.37±0.221 **↑

13 1310 1.234±0.042 2.294±0.227 **↑ 1.898±0.178 *↑

14 1234 1.904±0.173 3.704±0.286 **↑ 3.29±0.359 *↑

15 1152 0.634±0.114 1.996±0.141 ***↑ 1,99±0.151 ***↑

16 1080 1.452±0.066 3.107±0.046 ***↑ 2.852±0.092 ***↑ †↓

17 1045 1.594±0.132 3.616±0.126 ***↑ 2.938±0.114***↑ ††↓

18 1025 1.594±0.109 3.77±0.203 ***↑ 3.728±0.241 ***↑

19 925 0.142±0.016 0.276±0.03 **↑ 0.242±0.027 *↑

20 855 0.068±0.004 0.094±0.017 0.088±0.008

72

3.4.2.2.2. Comparison of Thalassemic and Healthy Control Bone Marrow

Mesenchymal Stem Cells in the 1800-800 cm-1 Region

The 1800-800 cm-1 contains several bands that originate from the protein,

carbohydrates, nucleic acid vibrational modes and from the interfacial and head

group vibrational modes of the membrane lipids (Mendelsohn and Mantsch, 1986).

Therefore, this region is called as fingerprint region.

The band located at about 1740 cm-1 is assigned to the >C=O ester stretching

vibration in phospholipids (Melin et al., 2000; Cakmak et al., 2003; Severcan et

al., 2003). The area of this band was significantly higher in pre-transplant group

BM-MSCs (0.48±0.01) (p<0.05) than the healthy controls (0.40±0.01). Following

BMT therapy, significant decline was observed in the post-transplant group BM-

MSCs (0.41±0.02) (p<0.05) with respect to the pre-transplant group.

The bands located at around 1639 cm-1 and 1545 cm-1 are attributed to the amide I

and amide II vibrational modes of structural proteins, respectively. The band at

1639 cm-1 (amide I) correspons to the C=O and C-N stretching (60%) modes of

vibrations weakly coupled with the N-H bending (40%) of the polypeptide and

protein backbone (Manoharan et al., 1993; Haris and Severcan, 1999). However;

the band at 1545 cm-1 (amide II) correspons to the N-H bending (60%) and the C-

N stretching (40%) modes of proteins (Melin et al., 2000; Takahashi et al., 1991;

Wong et al., 1991; Haris and Severcan, 1999; Cakmak et al., 2003). The band

area of amide I was significantly increased in pre-tranplant MSCs (19.22±0.366)

(p<0.05) when compared with the healthy control values (17.37±0.456). The area

of amide II band was significantly higher in both the pre-tranplant group MSCs

(11.78±0.759) (p<0.001) and post-transplant group MSCs (10.07±0.484) (p<0.01)

with respect to the healthy control group (7.158±0.339).

73

The CH2 bending vibrations of lipids are located at around 1453 cm-1 (Cakmak et

al., 2003; Di Giambattista et al., 2011) and COO− symmetric stretching vibrations

of fatty acid and amino acid side chains, at around 1400 cm−1 (Peuchant et al.,

2008; Cakmak et al., 2006; Melchiori et al., 2010). As can be seen from Table 3.3,

there were significant (p<0.001) increase in the areas of these two bands both in

the pre- and post-transplant group BM-MSCs. The band area values of post-

transplant group BM-MSCs diminished with respect to the pre-transplant group as

a result of transplantation therapy.

The band located at around 1310 cm-1 is attributed to amide II band components

and peptide side chains of protein structures (Yang et al., 2005; Fujioka et al.,

2004; Richter et al., 2002). The area of this band showed significant increase in

the pre-transplant (2.294±0.227) (p<0.01) and post-transplant group BM-MSCs

(1.898±0.178) (p<0.05) with respect to the healthy control BM-MSCs

(1.234±0.042).

The bands, which are located in the region between 1300-1000 cm-1, provide

insigth about several important macromolecules such as polysaccharides and

phosphate carrying compounds like phospholipids and nucleic acids (Melin et

al.,2000; Cakmak et al., 2003). The relatively strong bands at 1234 cm-1 and 1080

cm-1 are mainly due to the antisymmetric and symmetric phosphate stretching

modes, respectively. They are originated from phosphodiester groups in cellular

nucleic acids in addition to phospholipids, respectively (Rigas et al., 1990, Wong

et al, 1991; Wang et al, 1997; Cakmak et al., 2003). There were significant

increases in the area values of phosphate antisymmetric stretching band (1234cm-

1) of pre-transplant (3.704±0.286) (p<0.01) and post-transplant BM-MSCs

(3.29±0.359) (p<0.05) according to the healthy controls (1.904±0.173). Phosphate

symmetric stretching band (1080 cm-1) area also showed significant increases in

similar direction in the pre-transplant (3.107±0.046) (p<0.001) and post-transplant

74

BM-MSCs (2.852±0.092) (p<0.001). BMT therapy caused significant decrease in

the area of this band in post-transplant group (2.852±0.092) (p<0.05) with respect

to the control group (1.452±0.066). It has been reported that the three strong peaks

at 1025, 1045, 1152 cm-1 as a spectral contribution of glycogen might mask the

PO2- symmetric stretching band (Chiriboga et al, 2000; Cakmak et al, 2006). The

band at 1152 cm-1 is assigned to stretching mode of the CO-O-C groups in

glycogen and nucleic acids (Rigas et al, 1990; Cakmak et al, 2003). As can be

seen in Table 3.3, significant increases (p<0.001) were observed in the band area

for pre- and post-transplant group BM-MSCs. The bands at 1025 cm-1 and 1045

cm-1 are attributed to the vibrational frequencies of -CH2OH groups and the C-O

stretching frequencies coupled with C-O bending frequencies of the C-OH groups

of carbohydrates (including glucose, fructose, glycogen, etc. (Parker, 1971). We

observed significant increases (p<0.001) in the area of the bands located at 1025

cm-1 and 1045 cm-1 for pre- and post-transplant group BM-MSCs with respect to

the healthy control BM-MSCs (Figure 3.12 and Table 3.3).

The 1000-800 cm-1 wavenumber region is composed of spectral bands that are

originated from the CO stretching vibrations of protein structures and the

symmetric stretching mode of dianionic phosphate (PO3-2) monoester of nucleic

acids especially for DNA (Taillandier et al., 1992; Sahu et al., 2004; Lee et al.,

2009). Relatively weak spectral bands were observed at about 925 cm-1 and 855

cm-1 which were assigned as sugar vibrations in backbone of DNA-Z form and

vibrations in N-type sugars in nucleic acid backbone, respectively (Banyay and

Gräslund, 2003). The area of the band located at 925 cm-1 was significantly higher

in the pre-transplant BM-MSCs (0.276±0.03) (p<0.01) and post-transplant

(0.242±0.027) (p<0.05) when compared to the healthy control BM-MSCs

(0.142±0.016). As seen in Table 3.3, there were non- significant increases in the

area of 855 cm-1 band in pre and post-transplant groups with respect to the control

group.

75

The ratio of peak area values of the CH2 antisymmetric strectching band (2924 cm-

1) to the amide I (1639 cm-1) band was significantly higher (p<0.05) in the pre-

transplant group with respect to the control group MSCs (Table 3.4). The area

ratio of the bands located at 1045 cm-1 and 1545 cm-1 provide an information about

the carbohydrates such as glucose, fructose and glycogen etc. in the cells (Steiner

et al., 2003).

Table 3.4 Numerical summary of the detailed differences in the lipid-to-protein and carbohydrate-to-protein ratios of control and thalassemic BM-MSCs spectra. The values are the “mean ± standart error” for each sample. The degree of significance was denoted as *p<0.05 according to the healthy control group.

3.4.2.3. Cluster Analysis

The spectra of healthy, pre- and post-transplant group BM-MSCs showed

considerable differences as it was observed from general representative spectra of

thalassemic and healthy BM-MSCs in Figure 3.10. In this context, on the basis of

spectral differences in ATR-FTIR data, hierarchical cluster analysis was employed

to differentiate and characterize healthy, pre and post-transplant group BM-MSCs.

The analysis was applied to first-derivative and vector normalized spectra

belonging to the samples in three different regions namely 3050-800 cm-1, 3050-

2800 cm-1 and 1800-800 cm-1. The results of cluster analysis are demonstrated in

Figure 3.13, 3.14 and 3.15. As seen from the dendograms, all samples were

Ratio of band areas

Healthy Control

(n=5) Pre-Transplant

(n=5) Post-Transplant

(n=5)

(CH2 antisymmetric/ amide I) 0.142 ± 0.005 0.17 ± 0.007 *↑ 0.154 ± 0.007

(1045 cm-1/ amide II) 0.224 ± 0.022 0.316± 0.032 *↑ 0.294 ± 0.012

76

successfully distinguished for three different spectral regions. Higher

heterogeneity in cluster analysis demonstrates higher differences between

sampling groups. The heterogeneity value obtained from the cluster analysis in the

3050-800 cm-1 region was 1.2, in the 3050-2800 cm-1 region was 2 and in the

1800-800 cm-1 region was 1.6. Macromolecular alterations that were observed

from the spectral changes among control, pre- and post-transplant group BM-

MSCs were clarified and supported by cluster analysis. As seen from Figure 3.13,

there was only one misclassification in the cluster analysis belonging to the 3050-

800 cm-1 region. One of the sample from pre-transplant group that was marked

with ‡ mixed into post-transplant group. There were two misclassification in the

cluster analysis of the 1800-800 cm-1 region that is presented in Figure 3.15. One

sample from the control group and one sample from the post-transplant that were

marked with # mixed into pre-transplant group. These results revealed that

different groups can be successfully differentiated based on the spectral changes

obtained from ATR-FTIR spectroscopy by cluster analysis.

77

Figure 3.13 Hierarchical cluster analysis performed on the first-derivative and vector normalized spectra of control, pre- and post-transplant group BM-MSCs and resulting from Ward’s algorithm. The analysis was applied in the 3050-800 cm-1 spectral region. The mixed sample was marked with ‡.

‡

78

Figure 3.14 Hierarchical cluster analysis performed on the first-derivative and vector normalized spectra of control, pre- and post-transplant group BM-MSCs and resulting from Ward’s algorithm. The study was applied in the 3050-2800 cm-

1 spectral region.

79

Figure 3.15 Hierarchical cluster analysis performed on the first-derivative and vector normalized spectra of control, pre and post-transplant group BM-MSCs and resulting from Ward’s algorithm. The study was applied in the 1800-800 cm-1 spectral region. The mixed samples were marked with #.

80

3.4.2.4. FTIR Microspectroscopic Analysis and Comparison of Thalassemic

and Healthy Control Bone Marrow Mesenchymal Stem Cells

FTIR microspectroscopy provides spatially resolved information on unstained thin

tissue samples or cell monolayers by allowing the generation of IR images with

high image contrast. Unlike staining techniques, IR spectroscopy with its label-

free, non-invasive and non-destructive properties generates information about

relative concentrations and structure of macromolecules by considering alterations

in the infrared spectra and the specific heterogeneties (Krafft et al., 2006, Diem et

al., 2008). In this context, “FTIR imaging contains a multiplicity of contrast

yielding mechanisms that are derived from variations in the chemical composition,

without the addition of extrinsic markers or stains” (Lester et al., 1998).

In the first part of the study, the chemical maps of thalassemic and healthy control

BM-MSCs were obtained by FTIR microspectroscopy to get functional group

images of the main biological molecules of interest. Figures 3.16, 3.17, 3.18 and

3.19 show the chemical maps of pre-transplant, post-transplant thalassemic and

healthy MSCs. These figures were obtained using high resolution aperture size

(6.25µm x 6.25µm pixel size). Chemical maps that are obtained from IR

microspectroscopy allow us to track the distribution of chemical entities in

accordance with their relative absorbance intensity level for a chosen wavenumber

in a pixel-by-pixel fashion. In the chemical maps, the absorbance intensity is

proportional with the color changes that are represented by color scales from blue

(lowest intensity) to red (highest intensity).

The average colored chemical maps of lipids which was derived from the peak

integrated areas of the CH2 antisymmetric stretching and CH2 symmetric stretching

bands are seen in Figure 3.16 and 3.17, respectively. Each chemical map is

composed of thousands of spectra. The mean area values of mentioned bands from

81

the highest (red color) to lowest (blue color) concentrations are demonstrated by

absorbance values in color bars. As seen from the figures and the mean absorbance

values stated under the figures, lipid concentration of thalassemic BM-MSCs were

higher than healthy MSCs. Lipid contents in post-transplant group decreased after

BMT therapy. The changes in the lipid content that were obtained by IR

microspectroscopy similar with the ATR-FTIR spectroscopy results.

Control Pre-transplant Post-transplant

0.54±0.25 0.68±0.23 0.61±0.21

0.5 0.4 0.3 0.2 0.1 0

0.6

0.7

Figure 3.16 Spectral image maps of control, pre- and post-transplant BM-MSCs, which were derived from the peak integrated areas of CH2 antisymmetric stretching band, reflect lipid distribution in cells. Mean absorbance values of each map was given under the maps.

82

The protein distributions in control, pre- and post-transplant group BM-MSCs are

seen in Figure 3.18A and 3.18B. Chemical maps were derived by calculating

integrated area values of the amide I and amide II vibrational modes of structural

proteins, respectively. The absorbance values reflected that the protein content in

the BM-MSCs was higher in pre-transplant group BM-MSCs and decreased

following BMT therapy. The results of FTIR imaging supported the results of

ATR-FTIR spectroscopy.

Figure 3.17 Spectral image maps of control, pre and post transplant BM-MSCs, which were derived from the peak integrated areas of CH2 symmetric stretching band, reflect lipid distribution in cells. Mean absorbance values of each map was given under the maps.

Control Pre-transplant Post-transplant

0.2

0.15

0.1

0.05

0

0.16±0.07 0.21±0.08 0.18±0.09

83

5

4

3

2

1 0

4.3 ± 1.3 5.3 ± 1.7 4.9 ± 1.7

Control Pre-transplant Post-transplant

2.2±0.6 3.2±0.4 2.9±0.3

Control Pre-transplant Post-transplant

3.5

3

2

1

0.5

0

1.5

2.5

Figure 3.18 Spectral image maps of control, pre and post transplant BM-MSCs. A) Chemical maps were derived from the peak integrated areas of amide I and B) chemical maps were derived from the peak integrated areas of amide II band, reflect protein distribution in cells. Mean absorbance values of each map was given under the maps.

A

B

84

The distribution of nucleic acids in BM-MSCs is given in Figure 3.19. Chemical

maps of thalassemic and healthy control BM-MSCs were derived by calculating

integrated band area value of PO2- antisymmetric band. As it can be seen from the

figure, the nucleic acid content in the BM-MSCs was the highest in pre-transplant

group BM-MSCs and decreased after BMT therapy. These results are in agreement

with the results of ATR- FTIR imaging data

Control Pre-transplant Post-transplant

0.33±0.1 0.29±0.1 0.18±0.1

0.3

0.2

0.1

0.05

0

0.15

0.25

Figure 3.19 Spectral image maps of control, pre and post transplant BM-MSCs, which were derived from the peak integrated areas of PO2

- antisymmetric stretching band, reflects nucleic acid distribution in cells. Mean absorbance values of each map was given under the maps.

85

3.4.3. Comparison of Spectra of Bone Marrow Mesenchymal Stem Cells from

Different Age Groups

In the second part of the thesis study, molecular level differences or similarities

between healthy BM-MSCs from different age groups were investigated by FTIR

spectroscopy and microspectroscopy.

3.4.3.1. General Information about Numerical Comparisons of the Bands of

Bone Marrow Mesenchymal Stem Cells from Different Age Groups

The spectrum of each sample was analyzed by Spectrum 100 Software by

considering different spectral parameters like band frequencies, band widths and

band areas that were expressed in terms of “means and the standard errors”. Then

the data were evaluated by normality test in order to decide whether the parametric

or non-parametric statistical test to be used. Since the data showed normal

distribution, spectral measurements were compared to each other by using One

Way Anova and Tukey Multiple Comparison Test. Statistical significances were

conveyed in terms of p<0.05, p<0.01, p<0.001. The changes in band area values

are given in Table 3.5

3.4.3.2. Detailed Spectral Analysis of Bone Marrow Mesenchymal Stem Cells

from Different Age Groups

Figure 3.20 shows the general representative FTIR spectrum of the healthy human

BM-MSCs from different age donors in 3800-800cm-1 spectral region. As can be

seen from the quite complex spectrum that contains several bands representing

many different functional groups of lipids, proteins, carbohydrates and nucleic

acids. The positions of these bands are assigned in Table 3.1. The spectra of BM-

MSCs from all age groups were analyzed in two major regions; 3050-2800 cm-1

86

and 1800-900 cm-1. The baseline-corrected average spectra were used to perform

accurate measurements of the spectral parameters like band frequencies, band

widths and band areas. All spectra presented in the figures were normalized with

respect to the amide A band centered at around 3330 cm-1 for illustrative purposes.

3.4.3.2.1. Comparison of Bone Marrow Mesenchymal Stem Cells from

Different Age Groups in the 3050-2800 cm-1 region

Figure 3.21 represents the deconvolved and normalized FTIR spectra of BM-

MSCs from five different age groups in the 3000-2800 cm-1 region. This region

contains five main bands belonging to stretching modes of the olefinic =CH, CH2

and CH3 groups of unsaturated and saturated lipids. The bands at 2957 cm-1 and

2873 cm-1 are assigned to the CH3 antisymmetric and symmetric stretching

vibrations. The CH3 antisymmetric streching band originates mainly from lipids,

whereas CH3 symmetric stretching bands originates with th contribution of

proteins (Cakmak et al., 2011; Gorgulü et al., 2007; Takahashi et al., 2001). The

CH2 antisymmetric and symmetric stretching vibrations of methylene (-CH2)

groups of fatty acids are located at around 2924 and 2852 cm-1, respectively

(Kneipp et al., 2002; Melin et al., 2000; Cakmak et al., 2003).

87

88

89

90

The band area values under the spectral bands gives us an information about the

concentration of the corresponding functional groups (Kneipp et al., 2002; Bruno et

al., 1999; Krafft et al., 2007; Manoharan et al., 1993). As can ben seen in Table 3.5,

the band area values of the CH3 antisymmetric stretching band at 2957 cm-1 was

significantly higher in the children group (p<0.01) and adolescents group (p<0.001)

with respect to the infants group. The area of this band decreased significantly in

early adults (p<0.01) and mid adults BM-MSCs (p<0.01) in comparison to the area of

children group BM-MSCs. The area of this band decreased significantly in early

adults (p<0.001) and mid adults BM-MSCs (p<0.001) according to the area of

adolescents groups MSCs.

As seen from Figure 3.21 and Table 3.5, the area of the CH2 antisymmetric

stretching band of BM-MSCs increased significantly in the children group (p<0.001)

and the adolescents group (p<0.001) with respect to the infants group. Meanwhile,

the area of this band decreased significantly in early adults (p<0.001) and mid adults

(p<0.001) when they were compared with the area of children and adolescents groups

BM-MSCs.

As it is given in Table 3.5, the area values of the CH3 symmetric stretching band were

higher in children (p<0.05) and adolescents (p<0.01) groups with respect to the

infants group BM-MSCs. The area of this band decreased in early adults BM-MSCs

(p<0.05) and mid adults BM-MSCs (p<0.05) according to the value of children

groups BM-MSCs. Similarly, the area of this band decreased in early adults BM-

MSCs (p<0.01) and mid adults BM-MSCs (p<0.001) according to the value of

adolescents groups BM-MSCs.

The CH2 symmetric stretching band area was higher in adolescents group BM-MSCs

(p<0.01) with respect to infants groups BM-MSCs. The band area degrees decreased

91

in early adults BM-MSCs (p<0.01) and mid adults BM-MSCs (p<0.05) with respect

to children group BM-MSCs. The band area value of mid adults BM-MSCs

decreased significantly (p<0.05) when compared with the area value of adolescents

group (Table 3.5).

92

3.4.3.2.2. Comparison of Bone Marrow Mesenchymal Stem Cells from Different

Age Groups in the 1800-800 cm-1 region

In Figure 3.22, the 1800-900 cm-1 spectral region is shown. This region contains

vibrational modes of several distinct functional groups belonging to lipids, proteins,

carbohydrates and nucleic acids. The band centered at 1740 cm-1 is associated with

C=O stretching vibrations of esters bonds of tryglycerides (Mantsch, 1984; Steiner et

al., 2003; Cakmak et al., 2006). As it is given Table 3.5, the band area values of this

band were higher for children and adolescent group BM-MSCs than the infants, early

and mid adults BM-MSCs non-significantly. However, such an unsignificant increase

is in the same direction with the band area changes of other lipid bands located at

3000-2800 cm-1 spectral region.

93

94

The amide I band is located in the same region at around 1639 cm-1 which arises

from the C=O hydrogen bonded stretching and C=N bending vibrations (60%)

weakly coupled with the N-H bending (% 40) of polypeptides and protein

backbone. The another protein band, which is called as amide II at 1545 cm-1, is

assigned to the C-N stretching (40%) and NH bending vibrations (60%)

(Manoharan et al., 1993; Haris and Severcan, 1999). As it is shown in the Figure

3.22 and Table 3.5, amide I band and amide II band area values of BM-MSCs

were higher in children and adolescents groups than infants, early and mid adults

groups. The increases in the area of amide I band were significant in children

(p<0.001) and adolescents (p<0.001). However, significant decreases were

observed in the amide I band area of early adults MSCs (p<0.001) and mid adults

BM-MSCs (p<0.001) with respect to the area of children BM-MSCs. The amide I

band area also decreased significantly in mid adults BM-MSCs (p<0.001)

according to the adolescents BM-MSCs. Amide II band area value of adolescents

BM-MSCs were higher significantly (p<0.001) when compared with the value of

infants BM-MSCs. The area of amide II band, significanty decreased in early

adults (p<0.001) and mid adults (p<0.001) according to the children and

adolescents BM-MSCs.

From the FTIR spectrum, a precise lipid-to-protein ratio can be derived by

calculating the ratio of the areas of the bands arising from lipids and proteins. The

ratio was calculated as the ratio of the sum of the areas of the CH2 antisymmetric

and CH2 symmetric stretching bands to the area of the amide I band, which was

non-significantly lower in adolescents’s BM-MSCs (0.198±0.007) when it was

compared with infants’s BM-MSCs (0.211±0.011), children’s BM-MSCs

(0.202±0.005), early adults’s BM-MSCs (0.216±0.006) and mid adults’s BM-

MSCs (0.222±0.004). The decrease in the lipid to protein ratio reflected that there

was a more pronounced increase in protein content than an increase in the lipid

content. Elevated levels of lipid and protein contents in the adolescents BM-MSCs

95

with respect to the other groups were supported by the results of lipid to protein

ratio.

There were non-significant increases in the area of CH2 bending vibration of lipids

at 1453 cm-1 for children and adolescents BM-MSCs (Table 3.5) (Cakmak et al.,

2003; Manoharan et al., 2003). However, the area value of the band decreased

significantly in early adults BM-MSCs (p<0.05) and mid adults BM-MSCs

(p<0.01) with respect children BM-MSCs. Significant decreases in the area of this

band of early adults BM-MSCs (p<0.01) and mid adults BM-MSCs (p<0.001)

were also observed according to adolescents BM-MSCs (Table 3.5).

The band at 1401 cm-1 corresponds to the stretching vibration mode of C=O in the

COO- group of amino acid side chains and fatty acids (Krafft et al., 2007; Parker,

1971). The area of this band was higher in children and adolescent BM-MSCs than

the infants, early and mid adults BM-MSCs. Area of this band decreased

significantly in mid adults BM-MSCs (p<0.05) with respect to children and

adolescent BM-MSCs.

The band at 1310 cm-1 is assigned to amide III band components and peptide side

chain vibrations of protein structures (Yang et.al., 2005; Fujioka et al., 2004;

Richter et al., 2002). BM-MSCs of children and adolescents demonstrated higher

band area values, while significant decreases were observed in the area of mid

adults BM-MSCs (p<0.05) with respect of children and adolescent BM-MSCs.

The strong bands at 1234 cm-1 and 1080 cm-1 arise from antisymmetric and

symmetric stretching vibrations of phosphodiester groups that are present in the

phosphate moieties (PO2-) of nucleic acid backbone structures and phospholipids

(Melin et al., 2000, Rigas et al., 1990). Children and adolescents BM-MSCs had

significantly (p<0.01) higher PO2- antisymmetric stretching band area values with

96

respect to the infants BM-MSCs. As it is illustrated in Table 3.5, the lower band

area values for PO2- antisymmetric stretching band in early and mid adults BM-

MSCs were significant (p<0.001) according to the children and adolescents BM-

MSCs. Similar band area alterations were observed in the PO2- symmetric

stretching band is located at around 1080 cm-1. There was a significant decrease in

the band area degree of early adults and mid adults BM-MSCs (p<0.05) with

respect to children and adolescents BM-MSCs.

The area of the band at 1152 cm-1, which is due to stretching mode of the C-O-O-

C groups existing in glycogen and nucleic acids (Rigas et al., 1990; Cakmak et al.,

2003), was higher in children and adolescents BM-MSCs. The band area of early

adults (p<0.01) and mid adults (p<0.01) BM-MSCs tended to decrease

significantly when compared with the band area values of infants, children and

adolescents BM-MSCs. The other two bands located at about 1025 cm-1 and 1045

cm-1 are attributed from the vibrational frequency of -CH2OH groups and the C-O

stretching frequencies coupled with C-O bending frequencies of the C-OH groups

of carbohydrates (including glucose, fructose, glycogen, etc.) (Parker, 1971). As it

is given in Table 3.5, while increases in the area values of 1045 cm-1 band of

children (p<0.01) and adolescents (p<0.001) were significant with respect to

infants BM-MSCs, early adults (p<0.01) and mid adults (p<0.05) BM-MSCs

showed significant decreases with respect to the infants BM-MSCs. We also

observed significant decreases in the area of this band in early adults (p<0.001)

and mid adults (p<0.001) BM-MSCs according to the band area values of children

and adolescents BM-MSCs. Children (p<0.05) and adolescents (p<0.001) BM-

MSCs had also significantly higher intensity values for 1025 cm-1 band than

infants. On the contrary, early adults (p<0.01 and p<0.001) and mid adults

(p<0.01) BM-MSCs had lower band areas according to the children and

adolescents BM-MSCs, respectively.

97

The two bands at about 925 cm-1 and 855 cm-1 are assigned to sugar vibrations in

left handed Z type DNA (Dovbeshko et al., 2002). The area of these bands

increased in adolescent BM-MSCs significantly (p<0.05), (p<0.01) according to

the infants BM-MSCs. However, in early adult (p<0.05) and mid adults BM-

MSCs (p<0.05) band area values decreased significantly with respect to the

adolescent BM-MSCs.

3.4.3.3. Cluster Analysis

The spectra of BM-MSCs of infants, children, adolescents, early and mid adults

shows considerable differences as can be seen from Figure 3.20. Therefore,

hierarchical cluster analysis was employed to discriminate and characterize BM-

MSCs belonging to the different age groups healthy donors by evaluating the

spectral differences in ATR-FTIR data. The analysis was applied to first-derivative

and vector normalized spectra of twenty-five independent spectra of five sampling

groups in three different regions 3000-800 cm-1, 3000-2800 cm-1 and 1800-800 cm-

1. The results of cluster analysis are demonstrated in Figures 3.23, 3.24 and 3.25.

As seen from the dendograms, all samples were successfully distinguished for five

different spectral regions. Higher heterogeneity value in cluster analysis

demonstrates higher differences among analyzed groups. The heterogeneity value

obtained from the cluster analysis in the 3000-800 cm-1 region was 1.4 and one

sample from children group that was marked with # mixed into the adolescents

(Figure 3.23). The heterogeneity value of cluster analysis was 1 for 3000-2800 cm-

1 region and was 1.4 for 1800-800 cm-1 region. As seen from these two

dendograms, all samples were successfully distinguished for five sampling groups

as in distinct clusters. Cluster analysis verified and strengthened the spectral

differences that reflected significant macromolecular alterations among MSCs of

infants, children, adolescents, early and mid adults.

98

Figure 3.23 Hierarchical cluster analysis performed on the first-derivative and vector normalized spectra of BM-MSCs of infants, children, adolescents, early and mid adults, and resulting from Ward’s algorithm. The study was conducted in the 3000-800 cm-1 spectral region.

99

Figure 3.24 Hierarchical cluster analysis performed on the first-derivative and vector normalized spectra of BM-MSCs of infants, children, adolescents, early and mid adults, and resulting from Ward’s algorithm. The study was conducted in the 3000-2800 cm-1 spectral region.

100

Figure 3.25 Hierarchical cluster analysis performed on the first-derivative and vector normalized spectra of BM-MSCs of infants, children, adolescents, early and mid adults, and resulting from Ward’s algorithm. The study was conducted in the 1800-800 cm-1 spectral region.

101

3.4.3.4. FTIR Microspectroscopic Analysis and Comparison of Bone Marrow

Mesenchymal Stem Cells from Different Age Groups

The C-H region was used to evaluate the total lipid content in the cells. The

another band in this region is CH3 symmetric stretching band located at 2873 cm-1

that is mainly resulted from proteins. Since this band is very weak, the CH region

is concidered in terms of contribution of lipid bands. The average maps were

colored according to the peak integrated areas of CH2 antisymmetric and CH2

symmetric stretching bands that are two main lipid bands located in C-H region.

While red color corresponds to the highest ratio and blue color corresponds to the

lowest ratio in the color bar. The mean absorbance values of each map stated

under the figures. As it can be seen from the Figures 3.26 and 3.27, lipid

concentration of adolescent BM-MSCs was the highest value supporting to the

ATR-FTIR spectroscopy results.

0.76±0.31 0.84±0.34 0.93±0.39 0.71±0.47 0.68±0.33

Infants Children Adolescents Early Adults Mid Adults

0.6

0.2

0.1 0

0.3

0.4

0.5

0.8

0.9

1

Figure 3.26 Spectral image maps of BM-MSCs from five different age groups, which were derived from the peak integrated areas of CH2 antisymmetric stretching band, reflect lipid distribution in cells. Mean absorbance values of each map was given under the maps.

102

In order to examine protein distribution in BM-MSCs, chemical maps of cells

were constituted according to the integrated band area of amide I and amide II

bands from IR images. Figure 3.28 and Figure 3.29 show amide I and amide II

band area images, respectively. The difference in the protein contents can be

understand from the values of band areas that were stated under the chemical maps

of each group, in addition to the representative differences among chemical maps.

The absorbance values reflected that the protein content in the adolescents was

higher then the other sampling groups. The results of FTIR imaging are in

agreement with the results of ATR-FTIR spectroscopy.

Figure 3.27 Spectral image maps of BM-MSCs from five different age groups, which were derived from the peak integrated areas of CH2 symmetric stretching band, reflect lipid distribution in cells. Mean absorbance values of each map was given under the maps.

0.15±0.06 0.18±0.07 0.21±0.09 0.12±0.07 0.11±0.06

Infants Children Adolescents Early Adults Mid Adults

0

0.05

0.1

0.15

0.2

103

5

4

3

2

1

0

3.7±1.89 4.3±1.99 4.78±1.98 3.2±1.47 2.8±1.77

Infants Children Adolescents Early Adults Mid Adults

Figure 3.28 Spectral image maps of from five different age groups BM-MSCs, which were derived from the peak integrated areas of amide I band, reflect lipid distribution in cells. Mean absorbance values of each map was given under the maps.

Infants Children Adolescents Early Adults Mid Adults

0.8

1

1.2

0.4

0.2

0

0.6

1.4

1.6 1.8

1.2±0.77 1.3±0.72 1.7±0.77 0.96±0.57 0.89±0.49

Figure 3.29 Spectral image maps of from five different age groups BM-MSCs, which were derived from the peak integrated areas of amide II, reflect lipid distribution in cells. Mean absorbance values of each map was given under the maps.

104

The alterations in nucleic acid distribution in BM-MSCs from different age groups

were determined by considering the changes in PO2- integrated band area. As it is

given in the mean absorbance values (Figure 3.30), the nucleic acid concentration

of adolescents BM-MSCs was the highest degree according to the other groups.

The alterations in the concentration of nucleic acid in BM-MSCs from different

age groups were similar with the results of ATR-FTIR spectroscopy data.

3.5. MTT (Thiazolyl Blue Tetrazolium Bromide) Proliferation Assay

MTT proliferation assay was used to support FTIR spectroscopy results which

reflects global alterations in the concentrations of different macromolecules of P3

MSCs. These concentrational changes were interpreted as in the differences in

Infants Children Adolescents Early Adults Mid Adults

0.37±0.09 0.43±0.09 0.48±0.1 0.29±0.07 0.21±0.09

0

0.5

0.4

0.3

0.2

0.1

0.6

Figure 3.30 Spectral image maps of from five different age groups MSCs, which were derived from the peak integrated areas of PO2

- antisymmetric stretching band, reflect lipid distribution in cells. Mean absorbance values of each map was given under the maps.

105

metabolic and cellular activity of BM-MSCs. MTT proliferation assay is based on

the cleavage of the yellow MTT (3-(4.5-Dimethylthiazol-2-yl)-2.5-

diphenyltetrazolium bromide, a tetrazole) salt to purple formazan crystals in the

mitochondria of metabolically active and highly proliferative viable cells (Van de

Loosdrecht et al., 1994).

MTT proliferation assay was used into both topics of the thesis study that were

mentioned above. In the first part, thalassemic BM-MSCs before and after BMT

therapy and healthy control BM-MSCs were compared in terms of their cellular

activity by MTT assay during 11 days. Metabolic and cell proliferation activities

of healthy control and thalassemic BM-MSCs were measured at day 1, 3, 5, 7, 9

and 11 by measuring the purple solution of formazan crystals in SDS (sodium

dodesyl sulphate) by spectrophotometry at 620 nm wavelength. As it can be seen

in Table 3.6, the proliferation activity in thalassemic BM-MSCs was higher when

compared to the healthy controls. The cellular activity in post-transplant samples

decreased after BMT therapy. These results suggested that increase in the content

of macromolecules can be attributed to the increase in the cell proliferation activity

in thalassemic bone marrow microenvironment.

In the second part, the MTT assay was also applied to different aged BM-MSCs

during 11 days. Table 3.7 represents the results of MTT assay of healthy BM-

MSCs from different age groups. As can be seen from the table, adolescent group

had the highest cellular activity with respect to the other four age groups. Also the

cellular activity BM-MSCs of infans and children groups were higher. The results

showed that proliferative activity of BM-MSCs decreased by aging and we

observed that there were lower cellular activity in early and mid adults groups with

respect to the the younger infants, children and adolescent group BM-MSCs.

106

Table 3.6 MTT proliferation assay results of thalassemic and healthy control BM-MSCs at P3 during 11 days. The values were shown as ‘mean ± standard error’ for each group. The degree of significance was denoted as: *p<0.05 with respect to healthy control group.

Table 3.7 MTT proliferation assay results of P3 BM-MSCs obtained from healthy donors of different age groups. The values were shown as ‘mean ± standard error’ for each group. The degree of significance was denoted as: *p<0.05, **p<0.01, ***p<0.01 with respect to infants, †p<0.05, ††p<0.01, †††p<0.01 with respect to children, #p<0.05, ##p<0.01, ###p<0.01 with respect to adolescents.

Absorbance

Healthy Control

Group Pre-Transplant

Group Post-Transplant

Group Day 1 0.184±0.003 0.232±0.021 0.203±0.025 Day 3 0.225±0.013 0.299±0.019 *↑ 0.276±0.017 Day 5 0.262±0.024 0.331±0.009 0.312±0.021 Day 7 0.277±0.023 0.366±0.01 *↑ 0.329±0.025 Day 9 0.325±0.024 0.388±0.015 0.364±0.012 Day 11 0.338±0.029 0.400±0.013 0.374±0.016

Absorbance

Infants Children Adolescents Early Adults Mid Adults

Day 1 0.148±0,002 0.157±0.014 0.167 ± 0.002 0.141± 0.011 0.132 ± 0.005

Day 3 0.165±0.004 0.171±0,005 0.179 ± 0.002 0.156 ± 0.007 0.150 ±0.002†,###↓

Day 5 0.173±0.005 0.177±0.002 0.188± 0.001*↑ 0.163 ± 0.006##↓ 0.158±0.004††,###↓

Day 7 0,179±0.032 0.183±0.006 0.195±0.003 0.169 ± 0.001###↓ 0.165 ± 0.003

Day 9 0.185±0.003 0.191±0.003 0.21±0.003**,††↑ 0.176±0.003***,†,##↓ 0.170±0.003

*,†††,###↓

Day11 0.180±0.006 0.196±0.015 0.214±0.004*↑ 0.179±0.008 #↓ 0.173 ± 0.003 #↓

107

3.6. Erythropoietin (EPO) and Growth Differentiation Factor 15 (GDF 15)

Levels in Bone Marrow Plasma Samples

The levels of erythropoietin (EPO) and growth differentiation factor 15 (GDF 15)

in the bone marrow plasma samples is used to determine the level of massive

erythropoiesis and apoptotic pathways in hematological diseases such as

thalassemia. Spectral results in the first part of the study indicated that there was

an increase in cell proliferation activity in thalassemic bone marrow. The higher

cellular activity was supported by EPO and GDF 15 levels in bone marrow plasma

samples of thalassemic and healthy control BM-MSCs. EPO and GDF 15 levels in

bone marrow plasma samples of pre- and post-transplant thalassemia patients were

measured by Duo-Set Enzyme-Linked Immunosorbent Assay (ELISA). The

results of thalassemic BM-MSCs were compared with the results of healthy

controls. EPO levels were significantly higher in thalassemic patients before

tranplantation (44.91±12.30) (p<0.01) than the healthy control group (0.706±0.70).

However, EPO levels decreased significantly (10.71±2.13) (p<0.05) following

BMT therapy with respect to the pre-transplant group (44.9±12.30). ELISA results

of GDF 15 in bone marrow plasma samples showed similar alterations with EPO

results. GDF 15 levels of pre-transplant group BM-MSCs were significantly

higher (1466±407) (p<0.01) compared with the healthy controls (104.2±18.51).

On the other hand, significant decrease was measured in GDF 15 levels of post-

transplant group BM-MSCs (777.5±275.9) (p<0.05) after BMT therapy with

respect to pre-transplant group MSCs (1466±407).

108

CHAPTER 4

DISCUSSIONS

4.1. The Effects of Beta Thalassemia Major on Bone Marrow Mesenchymal

Stem Cells

In the first part of thesis study, the global molecular changes in the structure and

the composition of bone marrow mesenchymal stem cells (BM-MSCs) during beta

thalassemica major (β-TM) disease conditions were investigated by infrared

spectroscopy and microspectroscopy. The whole experimental results of pre- and

post-transplant thalassemic MSCs were compared with the healthy control BM-

MSCs. Meanwhile, the experimental results of post-transplant group BM-MSCs

were also compared with respect to the pre-transplant group in order to be able to

demonstrate the effects of bone marrow transplantation (BMT) therapy on

thalassemic BM-MSCs. Thalassemic and healthy BM-MSCs were characterized in

terms of according to their adherence to plastic surfaces of culture flask and their

fibroblast like morphology by considering the rules of ISCT (International Society

for Cellular Therapy) (Horwitz et al., 1999; Dominici et al., 2006). There was no

difference in morphological properties of thalassemic and healthy BM-MSCs. In

addition to that they were assessed for their expression of BM-MSCs CD105,

CD73 and CD90 surface antigens. Both thalassemic and healthy MSCs showed

≥95% expression for CD105, CD73 and CD90 antigens while they were lack of

expression for heamatopoietic markers CD45 and CD34. In accordance with the

ISCT criteria, differentiation capacities of thalassemic and healthy BM-MSCs into

109

osteoblasts and adipocytes were evaluated by using standart differentiation

inducing mediums. Thalassemic and healthy BM-MSCs differentiated into

adipogenic and osteogenic lineages and they stained by Oil red O and Alizarin Red

similarly (Figures 3.6 and 3.7).

Infrared spectra of biological samples contains some characteristic absorbtion

bands that belong to infrared-active vibrational modes of the different molecules.

These absorbtion bands represent different kinds of molecules in the sample like

carbohydrates, lipids, proteins and nucleic acids. Therefore, an infrared spectrum

of the biological sample provides valuable information about biochemical

structure of it. The typical wavenumbers, bandwidths and area values of these

bands give fingerprint-like information about functional groups in biomolecules.

The determination of mentioned spectral parameters enables us to characterize

detailed biochemical make-up of biological sample in non-destructively label-free

manner (Kneipp et al., 2000; Kretlow et al., 2006). The area of infrared bands of

particular functional groups is directly proportional to the concentration of them

(Ozek et al., 2009).

The level of unsaturation in the lipid acyl chains were examined by determining

the changes in the band area of olefinic band at 3010 cm-1 (Leskovjan et al., 2010;

Severcan et al., 2005; Krishnakumar et al., 2009). As it can be seen from Table

3.3, there was a significant increase in the area of this band in pre-transplant group

BM-MSCs when compared with the value of healthy control BM-MSCs. This

increase represents the increase in the amount of unsaturation in the acyl chains of

lipid molecules. The olefinic band area of the pre-transplant MSCs significantly

higher with respect to the post-transplant BM-MSCs (Leskovjan et al., 2010;

Severcan et al., 2005; Krishnakumar et al., 2009). This result demonstrated an

increase in the synthesis of unsaturated fatty acids that are known to have an

important role in cell proliferation by exerting growth supporting ability

110

(Kasayama et al., 1994). We also found an increase in the concentration of

saturated lipids that was determined by the analysis of the band area of CH2

antisymmetric and CH2 symmetric stretching bands originating from lipid acyl

chains. As shown in Table 3.3, the area degrees of these bands were significantly

(p<0.05) higher in the pre-transplant group BM-MSCs with respect to the healthy

control BM-MSCs. After BMT therapy, there was a tendecy to decline in the area

values of these bands towards the control group BM-MSCs. The increase in

saturated lipid content was further supported by the increase in the area of CH2

bending vibrations of lipids, at 1453 cm-1 (Cakmak et al., 2003, Di Giambattista et

al., 2011) and COO- symmetric stretching vibrations of fatty acid side chains, at

around 1400 cm-1 (Table 3.3) (Cakmak et al., 2006; Jackson et al., 1998; Peuchant

et al., 2008). The increase in saturated and unsaturated lipid contents may indicate

an increase in lipid synthesis in cells as a result of increased cellular activity.

Spectral alterations in the wavenumber (frequency) values of the absorption bands

give an information about the structure/conformation and intermolecular

interactions of that species (Jackson et al., 1997; 1999; Toyran et al., 2003). The

shifts in the band frequencies CH3 and CH2 antisymmetric, CH2 symmetric

stretching bands can be used as a marker for the detection of order/disorder states

of membrane lipids (Liu et al., 2002; Mantsch, 1984; Severcan et al., 1997). In

our study, the frequency of the CH3 antisymmetric stretching band shifted to lower

values both in pre- and post-transplant BM-MSCs compared to the control BM-

MSCs. These results reflected to increase in the order of the deep interior part of

the fatty acyl chains (Bruno, 1999) of thalassemic BM-MSCs. The changes in the

wavenumber of CH2 antisymmetric and symmetric stretching bands give

information about the chain fleixibility of fatty acids, which also reflects the

order/diorder status of the membrane lipids (Toyran et al., 2004; Melin et al.,

2000). As can be seen from Table 3.3, there was a significant decrease in the

wavenumber values of CH2 antisymmetric stretching band of pre- and post-

111

transplant BM-MSCs that reflected decrease in acyl chain flexibility. Such a

decrease in flexibility of fatty acids indicated an increase in the number of trans-

conformers of lipid molecules that was resulted in higher lipid order in membranes

(Severcan et al., 1997). The cells membranes have vital role in numerous functions

of cells such as adhesion, cell proliferation, differentiation, motility and

interactions with their microenvironment via signaling and metabolite traffic.

Therefore, the mechanical properties of cell membranes have been investigated in

many studies to get information about details of mentioned biological processes

(Emoto and Umeda 2001; Lundbaek et al., 2004; Titushkin et al., 2006). Active

and dynamic structure of cell plasma membrane provides specific cell shape

(Titushkin et al., 2006) which is affected from alterations in the lipid order (Moore

et al., 1997). According to the results of present study, the increase in the order of

membrane lipids in thalassemic BM-MSCs may effect membrane thickness and

cell shape which are important characteristics of the stem cell membrane in

mediating dynamic interactions with cellular microenvironment and external

stimuli particularly during bone marrow remodeling in disease conditions

(Titushkin et al., 2006; Spector et al., 1985).

As it can be seen from Figure 3.22 and Table 3.3, the area of amide I (1639 cm-1)

was significantly higher in pre-tranplant group (p<0.05) when compared with the

control group. The area of amide II mode (1545 cm-1) was increased significantly

both in the pre-tranplant (p<0.001) and post-transplant BM-MSCs (p<0.01) with

respect to the control BM-MSCs. These bands are mainly resulted from proteins

and alterations in their area and frequency values are used to monitor changes in

total protein content and structure of the cells (Manoharan et al., 1993; Haris and

Severcan, 1999). The significant increase in the area of the band located at aroun

1310 cm-1 which is assigned to peptide side chain vibrations (Steiner et al., 2003),

was used to support the data that were obtained from amide I and II. As noted in

ATR-FTIR data, there were significant increases in protein synthesis in

112

thalassemic BM-MSCs according to healthy control BM-MSCs and the increase in

the area of amide I and amide II bands was prominent in the pre-transplant BM-

MSCs than the post-transplant group. This finding was attributed to reduction in

total protein content and protein biosynthesis after BMT therapy. Existing studies

in the literature in accordance with the accumulation of protein in β-TM are

mainly about destruction of erythroid cells due to aggregation of free α-globin and

deficient hemoglobin production (Lithanatudom et al., 2010, Trombetta et al.,

2006, Khandros et al., 2010). However, there has been no specific investigation

about protein alterations in BM-MSCs in β-TM. The increase in protein content in

thalassemic BM-MSCs may also imply increased cellular activity in bone marrow

(BM) due to ineffective erytropoiesis. Khandros et al., 2010 suggested that β-TM

resembles protein aggregation disorders of the nervous system, liver and other

tissues.

As it is given in Table 3.4, the alteration in lipid to protein ratio was significantly

higher (p<0.05) in pre-transplant BM-MSCs with respect to the control BM-

MSCs. Such an increase in the lipid to protein ratio reflected that there was a

profound increase in the concentrations of lipids according to the increase in

protein concentrations of thalassemic BM-MSCs (Gorgulu, 2009). We can

concluded from that results, BM activity considerable affects lipid metobolism in

thalassemic BM-MSCs than protein metabolism.

The spectral region between 1300-1000 cm-1 contains infrared bands of the

stretching modes of phosphate moieties (PO2-) in phospholipids and nucleic acids

(Diem et al., 1999; Liquier and Taillandier, 1996). These phosphate-stretching

vibrations give an information about head-groups of the phospholipids in the

polar-nonpolar interface of cell membranes (Mendelsohn and Mantsch, 1986). In

addition to that they can be used to monitor variations in the quantity,

conformational state, degree and the position of phosphorylation of the nucleic

113

acids in DNA and RNA (Dovbeshko et al., 2000; Kneipp et al., 2000).

Antisymmetric phosphate stretching vibrations at 1234 cm-1 are mainly resulted

from nucleic acids, while symmetric-phosphate stretches at 1080 cm-1 assign C-O

skeletal stretching vibrations from nucleic acid sugars and C-O-P stretching

vibrations of phosphorylated lipids (Wood et al., 2000). As it is given in Table 3.3,

there were significant increases in the band area values of the antisymmetric and

symmetric phosphate stretching bands in pre-transplant and post-transplant group

with respect to the control group BM-MSCs. These results reflected an increases

in the concentrations of phospholipids and nucleic acids in thalassemic BM-MSCs.

Higher phosholipid concentration can be correlated with higher saturated and

unsaturated lipid contents in cells as a result of increased lipid biosynthesis in

abnormally active thallasemic bone marrow. The area of the band at 925 cm-1

which is assigned to Z type DNA (Banyay and Gräslund, 2003) was used to to

support nucleic acid related changes that were obtained from phosphate stretching

vibrations. The band area of this band (925 cm-1) was found significantly higher in

pre-transplant (p<0.01) and post-transplant group (p<0.05) thalassemic BM-MSCs

than the control MSCs. These findings, related with an increase in the nucleic acid

content, were suggested as a result of increased proliferation activity of

thalassemic BM-MSCs that was induced by ineffective erythropoiesis in

thalassemic BM microenvironment.

In the current study, significant increases in the area of the bands located at 1152

cm−1, 1045 cm-1 and 1025 cm-1, which are mainly resulted from carbohydrates

including glucose, fructose, glycogen and nucleic acids, were obtained in

thalassemic BM-MSCs (Parker, 1971; Cakmak et al., 2006). These significant

increases in the area of pre-transplant BM-MSCs (p<0.001) and also post-

transplant group BM-MSCs (p<0.001) revealed an enhanced glycogen and

carbohydrate concentrations in thalassemic BM-MSCs with respect to the control

BM-MSCs (Table 3.3). The area ratio of the bands located at 1045 cm-1 and 1545

114

cm-1 provides an information about carbohydrate levels such as glucose, fructose

and glycogen etc. in the cells (Parker, 1971) which was supported by higher

glycogen concentration in thalassemic MSCs with an increase in the ratio 1045

cm-1/1545 cm-1 (Table 3.4). These results were explained with increased synthesis

of glycogen in abnormally active thallasemic bone marrow because of ineffective

eythropoiesis. Previous studies in the literature reported that glycogen is used as an

alternative energy source in metabolic stress conditions of diseases like cancers to

enable cellular growth (Steiner et al., 2003, Emerman et al., 1980, Tsavachidou et

al.,2010). Significant increases in glycogen content of thalassemic cells with

respect to the healthy controls may support the increase in the content of other

macromolecules as a result of an enhanced cell proliferation in thalassemic bone

marrow microenvironment.

On the basis of the spectral variations, cluster analysis was also performed to

differentiate the control, pre- and post-transplant group thalassemic BM-MSCs.

The analysis was applied to the first-derivative and vector normalized spectra of

fifteen independent samples in three different regions, namely 3050-800 cm-1,

3050-2800 cm-1 and 1800-800 cm-1. As can be seen from the Figure 3.14, all

samples were successfully distinguished in 3050-2800 cm-1 region, while there

was only one misclassification for the cluster of 3050-800 cm-1 region (Figure

3.13) and there were two misclassification for the cluster of 1800-800 cm-1 (Figure

3.15). The higher heterogenity values for three different clusters implied that there

were important macromolecular alterations among control, pre- and post-

transplant group BM-MSCs. These results revealed that the spectral changes

obtained from ATR-FTIR spectroscopy can be successfully determined by cluster

analysis.

115

Thalassemic bone marrow dramatically expands during β-TM disease conditions

to get rid of deep anemic symptoms and iron accumulation (Melchiori et al.,

2010). This uncontrolable expansion of bone marrow is called as ineffective

erythropoiesis and it can be defined by increased level of erythropoietin (EPO) and

growth differentiation factor 15 (GDF15) in bone marrow plasma samples. Higher

level of EPO drive huge expansion of additional erythroid precursor with an

enhanced proliferative and survival capacity, while over expression of GDF15

controls differentiation and proliferation of erythroid precursors during ineffective

erythropoiesis (Melchiori et al., 2010; Lithanatudom et al., 2010; Ramirez et al.,

2009; Tanno et al., 2010). According to spectral results of the present study, we

made a suggestion that the global increases in the concentrations of different

macromolecules in thalassemic BM-MSCs with respect to the healthy controls can

be resulted from increased cell proliferation activity in abnormally active

thalassemic bone marrow. In this context, EPO and GDF15 levels were measured

in thalassemic and healthy bone marrow samples by ELISA assay, in order to

prove the existence of ineffective erythropoiesis in thalassemic bone marrows.

The EPO and GDF15 levels were found significantly higher in pre-transplant BM-

MSCs when compared with the healthy controls. However, following BMT

therapy the EPO and GDF15 levels of thalassemic patients showed tendency to a

significant decrease with respect to the pre-transplant patients. The higher EPO

and GDF15 levels in thalassemic bone marrow plasma samples before BMT

therapy were the robust indicators of abnormal erythropoietic activity of

thalassemic bone marrow as a response of bone marrow microenvironment to IE

that can be induced by secretory functions of BM-MSCs which are the main

cellular components of bone marrow microenvironment (Melchiori et al.,2010,

Lithanatudom et al., 2010). The significant decreases in the EPO and GDF15

levels after BMT therapy can indicate rapid adaptation of transplanted HSCs into

thalassemic bone marrow microenvironment and recovery effect of healthy HSCs

116

on thalassemic BM-MSCs as a result of cellular interactions in bone marrow

microenvironment. Therefore, the EPO and GDF15 levels were used to support

the results of ATR-FTIR spectroscopy which showed increased biosynthesis of

lipids, proteins, carbohydrates and nucleic acids because of increased cellular

activity in pre-transplant group thalassemic BM-MSCs. Additionally, the spectral

results showed that there were significant decreases in the concentrations of

mentioned macromolecules in post-transplant group BM-MSCs as a result of

diminished ineffective erythropoiesis and recovered abnormal cellular activity

after BMT therapy. MTT proliferation assay in Table 3.6 reflected that the

proliferation activity in thalassemic BM-MSCs was significantly higher than the

control MSCs. The cellular activity was still higher than the controls in the post-

transplant samples with the closer values to the healthy control group. These

findings were in the same direction with the results of ELISA assays. Such an

increased proliferation activity clarified higher concentration of macromolecules in

thalassemic BM-MSCs than the healthy control BM-MSCs.

Since post-transplant marrow samples were obtained shortly after engraftment

(between days +25 and day +35), the significant changes in BM-MSCs towards

normal values suggested that the interaction between hematopoetic and

mesenchymal cells is very dynamic, leading to a change in the abnormal patients

bone marrow microenvironment towards normal by achievement of healthy donor

eythropoesis following BMT. Therefore, the spectroscopic changes observed in

post-transplant group BM-MSCs can be used to interprete cellular interactions

between healthy HSCs and thalassemic BM-MSCs with an other supportive

experimantal data of ELISA and MTT proliferation assays. The significant

reductions in the concentrations of cellular macromolecules in post-transplant BM-

MSCs with respect to the pre-transplant BM-MSCs may reflects an adaptation of

patients’s BM-MSCs to the recovered bone marrow microenvironment by

decreasing cell proliferation rate and secretory activities after BMT therapy.

117

All these experimental results discussed above were performed according to the

suggestion that post-transplant group BM-MSCs were patients’s origin after BMT

therapy. Therefore; chimerism analysis was performed to determine whether the

origin of BM-MSCs belongs to the recipient or the donor after allogenic bone

marrow transplantation. Chimerism status of post-transplant samples can be

analyzed by fluorescence in situ hybridization (FISH) using X/Y gene probes in

sex-mismatched patients or short tandem repeat polymorphism analysis by

polimerase chain reaction (STR-PCR). In our study STR-PCR chimerism test was

used to analyze the polymorphic DNA loci of the donor and recipient cells. In

addition to that engraftment status was also determined by analyzing STRs of

donor, pre- and post-transplant recipient that are interspersed throughout the

genome. The unique but not the shared STR loci of the donor and recipient were

usually used to evaluate chimerism. As a result of chimerism test we found that

in all our 5 patients, MSCs were shown to be 100% recipient origin and BM-

MSCs of donor origin could not be detected. That is; BM-MSCs isolated from

recipients after allogenic BMT therapy, were not of donor genotype, despite the

presence of 95%-99% donor type hematopoietic engraftment in a short

engfraftment time. The earlier chimerism studies in literature showed that MSCs

remained of host origin (patient origin) even a long time after allogenic BMT

therapy while donor chimerism was achieved in HSCs (Rieger et al., 2005;

Villaron et al., 2004; Koc et al., 1999). In summary, our chimerism analysis

showed that even in short engraftment time (between +25 and +35 days) after

BMT therapy, adequate cellular interections between HSCs-MSCs can be achieved

to observe the healing of disease related alterations in patient’s bone marrow.

In addition to the β-TM disease related molecular alterations in BM-MSCs which

were indicated by using ATR-FTIR spectroscopy, FTIR imaging was also

118

performed by FTIR microspectroscopy for visual demontrations of the changes in

biochemical structure and composition in small sample regions on microscopic

scales (Szczerbowska-Boruchowska et al., 2007). Tens of thousands of individual

spectra can be collected rapidly and in parallel, each referring to a distinct and

identifiable spatial location on the sample. Besides the information about chemical

composition and molecular structure, which can also be obtained from

conventional IR spectra, the integration of spatial and spectral information in

vibrational imaging data sets provides representative demonstration of spectral

results (Lester et al., 1998). The band area of spectral vibrations originating from a

particular functional groups are directly proportional to the concentrations of

that species (Ozek et al., 2009). In this study, using FTIR imaging, the differences

in the distribution of concentrations of lipids, proteins and nucleic acids in MSCs

of control, pre- and post-transplant groups were demostrated representatively

which can also be used as a supportive data to the results ATR-FTIR spectroscopy.

The intensity/area changes of CH2 antisymmetric stretching and CH2 symmetric

stretching bands give an information about saturated lipid concentration in the

system (Severcan et al., 2000; Severcan et al., 2003; Cakmak et al., 2006). We

constituted the chemical maps of saturated lipids by taking the peak integrating

maps of the CH2 antisymmetric stretching and CH2 symmetric stretching bands. In

order to observe changes in concentrations of proteins, we constitute the chemical

maps by taking the area distrubition of bands arising from the C=O stretching

vibration of the amide I and N-H bending vibration of amide II (Manoharan

et al., 1993, Haris and Severcan 1999). In addition to these bands, the integrated

band area distrubition PO2- antisymmetric stretching of nucleic acids was used to

make a chemical maps of nucleic acid changes in the cells (Rigas et al., 1990,

Wong et al., 1991). For each sample belonging to the groups mentioned in the

results, the mean absorbance values of FTIR images were also calculated. It is

aimed to show that these mean absorbance values are in agreement with the results

119

based on the concentrational changes obtained by using ATR-FTIR. As it is given

in the mean absorbance in the Figures 3.16, 3.17, 3.18 and 3.19, there were an

increase in the concentrations of saturated lipids, proteins and nucleic acids in

thalassemic BM-MSCs according to healthy controls. Following BMT therapy, the

mean absorbance values of mentioned spectral bands decreased with respect to

pre-transplant group BM-MSC. The average chemical maps were colored

according to the intesity/area values of mentioned bands, where red color

corresponds to the highest ratio and blue color corresponds to the lowest ratio as

shown on the color bar in the figures. As it was observed from the color changes in

these chemical maps, pre-transplant groups BM-MSCs had the highest lipid,

protein and nucleic acid concentrations with respect to the post-transplant and

healthy control BM-MSCs. All these results belonging to the FTIR imaging study

were in agreement with the results of ATR-FTIR spectroscopy.

4.2. The Effects of Donor Age on Healthy Bone Marrow Mesenchymal Stem

Cells

In the second part of this study, effects of donor age on healthy BM-MSCs were

investigated by ATR-FTIR spectroscopy and FTIR microspectroscopy. Spectral

investigations were performed by using BM-MSCs from healthy donors which

were classified according to their ages in five different age groups labeled as

infant, children, adolescents, early and mid adults. Each group was statistically

compared with the remaining four groups in order to reveal the differences

between them.

Healthy BM-MSCs from different aged donors at passage 3 were characterized

with their adherence to plastic surfaces of culture flask and their fibroblast like

morphology. There were no difference in morphological properties and CD73,

CD90, CD105 expression profiles at passage 3. These results were supported by

120

the study of Mareschi et.al., 2006 where it was reported that there were no

differences in morphology and antigenic expression profiles of BM-MSCs of

young adult donors (range of age: 20-50) and pediatric donors (range of age: 6-11)

until passage 10. On the other hand, in the study of Huang et al., 2005, it was

demonstrated that BM-MSCs of fouetuses, 0-20 years old donors, 20-40 years old

donors, and donors older than 40 years old had similar morphology and antigenic

phenotype. In the scope of second part of the study, the cells from five different

age groups were characterized according to their adipogenic and osteogenic

differentiation capacities. Adipogenic and osteogenic differention was assessed by

using Oil red O and Alizerin Red staining, respectively. As seen in representative

(Figure 3.7 and 3.8) results, there were decreases in the adipogenic and osteogenic

differentiation potentials in early and mid adults (range of ages: 20-50) when

compared with the younger donors (range of ages: 0-19). The study of Kretlow et

al., 2008 showed that chondrogenic, osteogenic and adipogenic differentiation

potentials of cells from oldest donor decreased. In the study of Roura et al., 2006,

the effects of donor age on CD105+ mesenchymal stem cells in young (n=10,

24±6.4 years) and elderly (n=9, 77±8.4 years) donors were investigated. They

reported non-significant decrease in adipogenic differentiation potential by Oil

Red O staining and significant decrease in osteogenic differentiation potentials by

von Kossa staining in elderly donors. Although most of the existing studies

support our results, there are many conflicting data available in the literature about

the effects of aging on the differentiation potentials of MSCs since the donors and

the sample models used in these studies were different.

There is limited information about how donor age affects the fate of stem cells and

whether the changes caused by aging alter the stem cell niche (Campisi and

Sedivy, 2009). Stem cells are required for homeostasis and tissue regenaration. It

is thought that impaired tissue homeostasis and regenaration capacity can be

assumed to be arising from alterations in the number and/or function of stem cells

121

(Beltrami et al., 2011; Rando, 2006). In this context, the question arises whether

age related changes are due to the intrinsic aging of stem cells or due to the aged

stem cell microenvironment (niche) (Wagner et al., 2008). Age-related alterations

in stem cells and their external environment should be investigated in order to

standardize quality products and cellular therapies. Up to now, the numbers of

passages and population doublings, and senescence-associated molecular changes

have not been clarified whether they are tolarable to optimize therapeutic effects of

clinical applications. These findings make it inevitable to define a reliable and

easy method to track cellular aging of MSCs (Wagner et al., 2010; Stolzing and

Scutt, 2006). Studies in the literature have reflected that cellular senescence does

not significantly effect the viability, morphology, function, proliferation and

differentiation capacity of cells, while it causes decline in cellular metabolism

(Wagner et al., 2008; 2010; Stolzing and Scutt, 2006). Until now senescence

associated β-galactosidase (SA-β-gal) has been used to determine senescence.

Although SA-β-gal is overexpressed and accumulates specifically in senescent

cells, it is not the only marker of senescence. The enlarged and apoptotic cells in

higher passages also become SA-β-gal positive. This means that β-galactosidase

activity is associated with mainly replicative senescence in-vitro (Wagner et al.,

2010; Stolzing, A., and Scutt, A., 2006). The study of Stolzing and Scutt, 2006

showed that there was no correlation between the age of organism and the level of

SA-β-gal staining in fresh ex-vivo or in-vivo tissue. In summary, no specific

molecular marker is available to determine the degree of cellular aging in MSCs.

In this context, we hyphothesized that IR spectroscopy as a novel, non-destructive

research method with its real-time chemical monitoring and high-quality data

collection properties, can be used to identify molecular marker(s) reflecting the

stem cell aging.

122

Spectral region between 3000-2800 cm-1 was used to determine the level of

saturation in the lipid acyl chains by examining the changes in the CH3, CH2

antisymmetric and CH2 symmetric stretching bands (Severcan et al., 2005;

Krishnakumar et al., 2009; Leskovjan et al., 2010). As it is shown in Table 3.5,

there were significant increases in these bands for children and adolescents groups

when compared with the other groups. These increases indicate an increase in the

amount of saturation in the acyl chains of lipid molecules as a result of increase in

synthesis of saturated fatty acids that are known to have an important role in cell

proliferation by exerting growth supporting ability (Kasayama et al., 1994). The

increase in saturated lipid content was further supported by the increase in the area

of CH2 bending vibrations of lipids, at 1453 cm-1 (Cakmak et al., 2003; Di

Giambattista et al., 2011) and COO- symmetric stretching vibrations of fatty acid

side chains, at around 1400 cm-1 (Table 3.5) (Peuchant et al., 2008; Cakmak et al.,

2006; Jackson et al., 1998). These two bands were slightly higher for children and

adolescents MSCs. These increases in saturated lipid concentrations in children

and adolescents may indicate an increase in lipid synthesis in cells as a result of

increased metabolic activity.

Changes in the band areas of amide I, amide II and amide III reflected the

alterations in the protein concentrations in cells. As it is shown in Table 3.5, for

children and adolescents groups, the band area values of amide I and amide II

were significantly higher while was non-significantly higher for the amide III. As

noted in ATR-FTIR data, there were significant increases in protein synthesis in

children and adolescents MSCs when compared with the infants, early and mid

adults MSCs. Significant decreases in the area values of amide I, amide II and

amide III bands for early and mid adults leaded to the decrease in protein synthesis

in these groups.

123

The changes in lipid to protein ratio were non-significant. This ratio slightly

decreased in children and adolescents group MSCs with respect to infants, early

and mid adults MSCs. Such a decrease in the lipid to protein ratio meaned that

there may be a profound increase in the protein concentration compared to the

increase in lipid concentration in MSCs (Gorgulu, 2009). By using these findings,

we concluded that the increase in cellular activity considerably affected protein

metobolism in healthy MSCs than the lipid metabolism.

The area changes in the infrared bands of PO2- antisymmetric vibrations at 1234

cm-1 and symmetric stretching vibrations at 1080 cm-1 were used to investigate the

variations in the quantity, conformational state, degree and the position of

phosphorylation of the nucleic acids in DNA and RNA (Dovbeshk et al., 2000;

Kneipp et al., 2000). As it can be seen in Table 3.5, there were significant

increases in the band area values of the antisymmetric phosphate stretching bands

for children and adolescents groups MSCs when compared with the infant group

MSCs. However, non-significant increases were observed in the PO2- symmetric

stretching band areas for the same groups. The bands at 925 cm-1 and 855 cm-1

were used to support nucleic acid related changes. The area values in these bands

were significantly higher for adolescent MSCs and non-significantly higher for

children MSCs. There were significant decreases in the area of these four bands

for early and mid adults MSCs with respect to the adolescents and children MSCs.

The findings about an increase in the nucleic acid content were suggested to be

resulting from increased proliferative activity of adolescents and children MSCs.

There were significant increases in the areas of the bands at 1152 cm−1, 1045 cm-1

and 1025 cm-1, for children and adolescent MSCs. These increases mainly resulted

from carbohydrates including glucose, fructose, glycogen and nucleic acids

(Parker, 1971; Cakmak et al., 2006). These findings indicated enhanced glycogen

124

and carbohydrate concentrations in children and adolescent MSCs, whereas

significant declines were observed in early and mid adult MSCs (Table 3.5).

MTT proliferation assay was carried out in order to prove increased cellular

activity. The results of MTT proliferation assay was used to support the data

obtained from ATR-FTIR spectroscopy. As it is given in Table 3.7, MTT

proliferation assay results showed that the proliferation activity in adolescents

MSCs were significantly higher than the activities in other sample groups MSCs.

It was shown that the children and infant MSCs also had an higher level of

proliferative activity than early and mid adults MSCs. We observed significant

decreases in proliferation capacity in cells of early and mid adults. Mareschi et al.,

2006 found that cell growth was related to the age of donors. Their study reflected

that MSCs of pediatric donors (range of age: 6-11) were proliferate twice as high

as MSCs of adult donors (range of age: 20-50). Scutt et al., 1996 investigated the

age effect on rats whose ages were 3, 7, 12 and 56 weeks. They found that

apoptosis and reduced proliferation capacity levels were higher in the cells of older

rats.

On the basis of the spectral variations, cluster analysis was also performed to

discriminate MSCs of infants, children, adolescents, early and mid adults. The

analysis was applied to the first-derivative and vector normalized spectra of twenty

five samples in three different regions of 3000-800 cm-1, 3000-2800 cm-1 and

1800-800 cm-1. As seen in Figures 3.23, 3.24 and 3.25, there was only one

misclassification for the cluster of 3000-800 cm-1 region while all samples were

successfully distinguished in clusters of 3000-2800 cm-1 and 1800-800 cm-1

regions. The higher heterogenity values for three different clusters implied that

there were important macromolecular alterations among the MSCs of different age

groups. These results revealed that the spectral changes obtained from ATR-FTIR

spectroscopy can be successfully determined by cluster analysis.

125

In this part of the study, we used FTIR spectroscopy as a novel method to

determine unique molecular marker(s) in order to identify the effects of donor age

on bone marrow MSCs. We observed some differences in the concentrations of

cellular macromolecules. These findings were interpreted as the differences in the

proliferative activity of cells in accordance with the age differences of donors.

These interpretations were supported by MTT assay results that were in

accordance with the ATR-FTIR data.

As an other supportive method, FTIR microspectroscopy was used. This method is

known to be providing information about biochemical structure and composition

of cells in a small sample region with microscopic scales (Szczerbowska-

Boruchowska et al., 2007). The differences in the distribution of concentration of

lipids, proteins and nucleic acids in MSCs of five different age groups were

demonstrated representetively. The intensity/area changes of the CH2

antisymmetric stretching and CH2 symmetric stretching bands give an information

about saturated lipid concentration in the system (Severcan et al., 2000; Severcan

et al., 2003, Cakmak et al., 2006). We constituted the chemical maps of saturated

lipids by using the peak integrating maps of the CH2 antisymmetric stretching and

CH2 symmetric stretching bands. In order to observe the changes in concentrations

of proteins, we constitute the chemical maps by using the area distribution of

bands which arises mainly from the C=O stretching vibration of the amide I and

N-H bending vibration of amide II (Manoharan et al., 1993, Haris and Severcan

1999). In addition to these bands, the integrated band area distribution of PO2-

antisymmetric stretching of nucleic acids was used to make a chemical map of

nucleic acid changes in the cells (Rigas et al., 1990; Wong et al., 1991). As it is

given in the mean absorbance values in Figures 3.26, 3.27, 3.28, 3.29 and 3.30, the

concentrations of saturated lipids, proteins and nucleic acids for children and

adolescents groups were higher when compared with the infants, early and mid

adults. The mean absorbance values in these spectral bands were lower for older

126

donors. The average chemical maps were colored according to the intensity/area

values of mentioned bands where red color corresponds to the highest ratio and

blue color corresponds to the lowest ratio as shown on the color bar in the figures.

As it was understood from the color changes in these chemical maps,

concentrational changes can be ordered from higher to lower values as

adolescents, children, infants, early and mid adults. All the results obtained from

FTIR imaging study were in agreement with our ATR-FTIR data and allowed the

generation of IR maps with high image contrast as a supportive data.

127

CHAPTER 5

CONCLUSION

In the first part of the study, it was aimed to investigate the molecular level

changes in human bone marrow mesenchymal stem cells (BM-MSCs) in

pathological bone marrow microenvironment during disease beta thalassemica

major (β-TM). The results of the study showed that β-TM had significant

influence on the structure and the concentration of biological macromolecules and

secretory functions of BM-MSCs. However, β-TM did not cause any changes on

the main characteristics of cells that were used to define BM-MSCs. Thalassemic

and healthy BM-MSCs had similar cellular morphology under inverted light

microscope. Their expression profile for CD105, CD90, CD73, CD45 and CD34

surface antigens were also similar. Both thalassemic and healthy BM-MSCs were

differentiated into adipocytes and osteocytes. The spectral results showed that

there were significant increases in the contents of saturated and unsaturated lipids,

protein, glycogen and nucleic acids in thalassemic BM-MSCs. Lipid order in cell

membrane also increased in thalassemic BM-MSCs. These results suggested that

increase in the concentration of macromolecules can be attributed to the increase

in the proliferation activity of cells during ineffective erythropoiesis in thalassemic

bone marrow. Erythropoietin (EPO) and growth differentiation factor 15 (GDF 15)

levels and MTT proliferation assay results were used in order to support ATR-

FTIR results and determine the degree of ineffective erythropoiesis. The

concentration of macromolecules in post-transplant BM-MSCs was shown to be

decreased when compared to the pre-transplant BM-MSCs. On the other hand,

128

EPO and GDF15 levels, and proliferation activity in the MTT assay results

following bone marrow transplantation (BMT) therapy were shown to decrease for

the case of post-transplant BM-MSCs as well. All of these results could be

interpreted as a decrease in cellular activity as a result of restoring effect of BMT

therapy on abnormal erythropoiesis by leading the normalization of abnormal host

microenvironment.

The chimerism test, which was performed +25 and +35 days after transplantation,

showed that there were complete donor type hematopoietic engraftment in the

patients’s bone marrows while BM-MSCs remained 100% recipient (patient)

origin. The restoring effect of BMT therapy observed during attenuated total

reflection Fourier transform infrared (ATR-FTIR) spectroscopy study can be used

to identify hematopoietic stem cells (HSCs) and BM-MSCs dynamic interactions

in bone marrow microenvironment. The results of the ATR-FTIR spectroscopy

study were also supported by FTIR imaging which was used to demonstrate

distribution of macromolecules in the cells as in chemical maps. Thalassemic and

healthy control BM-MSCs were successfully separated by using the hierarchical

cluster analysis where alterations in structure and composition of macromolecules

obtained from FTIR data were considered. These results showed the differences

between thalassemic and healthy control BM-MSCs. Moreover, they provided

better understanding of the in-vivo cell-to-cell interactions between HSCs and

MSCs. Therefore, this study became to be the first model study which may

contribute to future studies for investigating cellular interactions in the bone

marrow microenvironment.

In the second part of the study, we aimed to identify new molecular marker(s) in

order to determine the effects of donor age on healthy BM-MSCs. The results

showed that donor age had significant influence on the concentrations of important

macromolecules existing in the cells. The BM-MSCs from healthy donors in

129

different ages had similar cellular morphology under inverted light microscope at

passage 3. Also, their expression profiles for CD105, CD90, CD73, CD45 and

CD34 surface antigens were same. In addition to this, adipogenic and osteogenic

differentiation potentials of older MSCs were lower when compared to the

younger cells representatively. The spectral results reflected that there were

significant increases in the concentration of saturated lipids, proteins, glycogen

and nucleic acids in children and adolescent group BM-MSCs when compared to

the infants, early and mid adults. The concentrations of mentioned

macromolecules in early and mid adults BM-MSCs were significantly lower than

the concentrations in the children and adolescents BM-MSCs. These increases in

the concentrations of macromolecules were decided to be a result of the increase in

the proliferation activity in younger BM-MSCs. The cellular activity degree was

determined through the MTT proliferation assay results and this was used to

support ATR-FTIR spectroscopy results. The MTT assay results showed that BM-

MSCs obtained from younger donors, such as infants, children and adolescents,

had higher cellular activity than the BM-MSCs obtained from early and mid

adults. FTIR microspectroscopy revealed the distribution of macromolecules in the

cells as chemical maps whose results also are in agreement with the ATR-FTIR

results. BM-MSCs of five different age groups were discriminated by making the

hierarchical cluster analysis where the ATR-FTIR spectroscopy data according to

alterations in structure and composition of macromolecules were considered.

130

REFERENCES

Aerts, F.S.F., and Wagemaker, G., (2004). Mesenchymal stem cell engineering

and transplantation, Springer, Dordrecht, The Netherlands , 1-44. Aggarwal, S., (2003). Stem cell tranplantation in thalassemia. Int. J. Hum. Genet., 3: 205-208. Aggarwal, S., and Pittenger, M.F., (2005). Human mesenchymal stem cells modulate allogeneic immune cell responses. Blood, 15: 1815-1822. Akkas, S.B., Severcan, M., Yilmaz, O., and Severcan, F., (2007). Effects of lipoic acid supplementation on rat brain tissue: An FTIR spectroscopic and neural network study. Food Chem., 105: 1281-1288. Akkas, S.B., Inci, S., Zorlu, F., and Severcan, F., (2007). Melatonin affects the order, dynamics and hydration of brain membrane lipids. J. Mol. Struct., 834: 207-215. Ami, D., Neri, T., Natalello, A., Mereghetti, P., Doglia, S.M., Zanoni, M., Zuccotti, M., Garagna, S., and Redi, C.A., (2008). Embryonic stem cell differentiation studied by FT-IR spectroscopy, Biochimica et Biophysica Acta., 1783: 98–106. Angelucci, E. and Baronciani, D., (2008). Allogeneic stem cell transplantation for thalassemia major. Heamatologica, 93: 1780-1784. Argov, S., Ramesh, J. Salman, A., Sinelnikov, I., Goldstein, J., Guterman, H., and Mordechai, S., (2002). Diagnostic potential of Fourier-transform infrared microspectroscopy and advanced computational methods in colon cancer patients. J. Biomed. Opt., 7: 248-254. Asanuma, H., Meldrum, D.R., and Meldrum, K.K., (2010). Therapeutic applications of mesenchymal stem cells to repair kidney injury. J. Urol., 184: 26-33 Askmyr, M., Quach, J., Purton, E.L., (2011). Effects of the bone marrow microenvironment on hematopoietic malignancy. Bone, 48: 115-120.

131

Babrah, J., McCarthy, K., Lush, R.J., Rye, A.D., Bessant C., and Stone, N., (2009). Fourier transform infrared spectroscopic studies of T-cell lymphoma, B-cell lymphoid and myeloid leukaemia cell lines. Analyst, 134: 763-768. Baksh, D., Song, L., and Tuan, R.S., (2004). Adult mesenchymal stem cells: Characterization, differentiation, and application in cell and gene therapy. J. Cell. Mol. Med., 8(3): 301-316. Banyay, M., and Gräslund, A., (2003). A library of IR bands of nucleic acids in solution. Biophys. Chem., 104: 477-488. Barry, F.P., (2003). Biology and clinical applications of mesenchymal stem cells. Birth Defects Res. C. Embryo Today, 69: 250-256. Bartsch, K., Al-Ali, H., Reinhardt, A., Franke, C., Hudecek, M., Kamprad, M., Tschiedel, S., Cross, M., Niederwieser, D., and Gentilini, C., (2009). Mesenchymal stem cells remain host-derived independent of the source of the stem-cell graft and conditioning regimen used. Transplantation, 87: 217-221. Baxter, M.A., Wynn, R.F., Jowitt, S.N., Wraith J.E., Fairbairn, L.J., and Bellantuono, I., (2004). Study of telomere length reveals rapid aging of human marrow stromal cells following in vitro expansion. Stem Cells, 22: 675-682. Becerra, J., Santos-Ruiz, L., Andrades, J.A., Marí-Beffa, M., (2011). The stem cell niche should be a key issue for cell therapy in regenerative medicine. Stem Cell Rev., 7: 248-255. Bechtel, H.A., Martin, M.C., May, T.E., and Lerch, P., (2009). Improved spatial resolution for reflection mode infrared microscopy. Rev. Sci. Instrum., 80: 126106. Beier, J.P., Bitto, F.F., Lange, C., Klumpp, D., Arkudas, A., Bleiziffer, O., Boos, A., Horch, R.E., and Kneser, U., (2010). Myogenic differentiation of mesenchymal stem cells co-cultured with primary myoblasts. Cell Biol. Int., 35: 397-406. Beltrami, A.P., Cesselli, D., and Beltrami, C.A., (2011). At the stem of youth and health. Pharmacol Ther., 129: 3-20. Birgens, H., and Ljung, R., (2007). The thalassaemia syndromes. Scand. J. Clin. Lab. Invest., 67: 11-25.

132

Bizeau, M.E., Salano, J.M., and Jeffrey, R., (2000). Menhaden oil feeding increases lypolysis without changing plasma membrane order in isolated rat adipocytes. Nutrition Research, 20: 1633-1644. Bozkurt, O., Bilgin, M.D., and Severcan, F., (2007). The effect of diabetes mellitus on rat skeletal Extensor digitorum longus muscle tissue: An FTIR study, Spectroscopy - Int. J., 21: 151-160. Bozkurt, O., Severcan, M., Severcan, F., (2010). Diabetes induces compositional, structural and functional alterations on rat skeletal soleus muscle revealed by FTIR spectroscopy: a comparative study with EDL muscle. Analyst, 135: 3110-3119. Bruno, T.J., (1999). Sampling accessories for infrared spectrometry. Appl. Spectr. Rev., 34: 91–120.

Bullen, H.A., Oehrle, S.A., Bennett, A.F., Taylor, N.M., and Barton, H.A., (2008). Use of attenuated total reflectance Fourier transform infrared spectroscopy to identify microbial metabolic products on carbonate mineral surfaces. Appl. Environ. Microbiol., 74: 4553-4559.

Cakmak, G., Zorlu, F., Severcan, M., Severcan, F., (2011). Screening of protective effect of amifostine on radiation-induced structural and functional variations in rat liver microsomal membranes by FT-IR spectroscopy. Anal Chem., 83: 2438-2444.

Cakmak, G., Togan, I., and Severcan, F., (2006). 17β-Estradiol induced compositional, structural and functional changes in rainbow trout liver, revealed by FT-IR spectroscopy: A comparative study with nonylphenol. Aquatic. Tox., 77: 53–63.

Cakmak, G., Togan I., Uğuz, C., and Severcan, F. (2003). FT-IR spectroscopic analysis of rainbow trout liver exposed to nonylphenol. Appl. Spectr., 57: 835-841.

Campbell, J.D., and Dwek, R.A., (1984). Biological Spectroscopy. The Benjamin/ Cummings Publishing Company, Inc.

Campisi, J., Sedivy, J., (2009). How does proliferative homeostasis change with age? What causes it and how does it contribute to aging? J. Gerontol. Biol. Sci. Med. Sci., 64: 164-166.

Caplan, A.I., (2000). Mesenchymal stem cells and gene therapy. Clin. Orthop. Relat. Res., 379: 67-70.

133

Caplan, A.I., (2009). Why are MSCs therapeutic? New data: new insight. J. Pathol., 217: 318–324.

Chan, J.W., and Lieu, D.K., (2009). Label-free biochemical characterization of stem cells using vibrational spectroscopy. J. Biophotonics, 2: 656–668.

Chan, J.W., Lieu, D.K., Huser, T., and Li, R.A., (2009). Label-free separation of human embryonic stem cells (hESCs) and their cardiac derivatives using Raman spectroscopy. Anal. Chem., 81: 1324–1331.

Chang, M.C., Tanaka, J., (2002). FT-IR study for hydroxyapatite/collagen nanocomposite cross-linked by glutaraldehyde. Biomaterials, 23: 4811–4818.

Chen, D.P., Tseng, C.P., Tsai, S.H., Wu, T.L., Chang, P.Y., Sun, C.F., (2008). Systematic analysis of stutters to enhance the accuracy of chimerism testing. Ann Clin Lab Sci., 38: 264-272.

Ci, X.Y., Gao, T.Y., Feng, J., and Guo, Z.Q., (1999). Fourier transform infrared characterization of human breast tissue: Implications for breast cancer diagnosis. Appl. Spectr., 53: 312-315.

Cole, K.C., (2009). The use of attenuated total reflection infrared spectroscopy to study the intercalation of molten polymer into layered silicates in real time. Appl. Spectr., 63: 1343-1350.

Coleman, P.B., (1993). Practical Sampling Techniques for: Infrared Analysis. CRC Press.

Colthup, N.B., Daly, L.H., and Wiberley, S.E., (1975). Introduction to infrared

and raman spectroscopy. New York: Academic Press. Dennis, J.E., and Caplan. A.I., (2004). Advances in mesenchymal stem cell biology. Current Opinion in Orthopaedics, 15: 341-346. Di Giambattista, L., Pozzi, D., Grimaldi, P., Gaudenzi, S., Morrone, S., and Castellano A.C., (2011). New marker of tumor cell death revealed by ATR-FTIR spectroscopy. Anal. Bioanal. Chem., 399: 2771-2778. Dicko, A., Morissette, M., Ameur, S.B., Pezolet, M., and Di Paolo, T., (1999). Effect of estradiol and tamoxifen on brain membranes: investigation by infrared and fluorescence spectroscopy. Brain Res. Bull., 49: 401-405.

134

Diem, M., Boydston-White, S., and Chiriboga, L., (1999). Infrared spectroscopy of cells and tissues: shining light onto a novel subject. Appl. Spectr., 53: 148-161. Diem, M., Romeo, M.J., Mattheaus C., Miljkovic, M., Miller, L., and Lasch, P., (2004). Comparison of Fourier transform infrared (FTIR) spectra of individual cells acquired using synchrotron and conventional sources. Infrared Physics &

Tech., 45, 331---338.

Diem, M., Chalmers, J.M., and Griffiths, P.R., (2008). Vibrational spectroscopy

for medical diagnosis. John Wiley & Sons, Chichester, England; Hoboken, NJ. Dogan, A., Ergen, K., Budak, F., and Severcan, F., (2007). Evaluation of disseminated candidiasis on an experimental animal model: a Fourier Transform Infrared study. Appl. Spectr., 61: 199-203. Dominici, M., Le Blanc, K., Mueller, I., Slaper-Cortenbach, I., Marini, F.C., Krause, D.S., Deans, R.J., Keating, A., Prockop, D.J., and Horwitz, E.M., (2006). Minimal criteria for defining multipotent mesenchymal stromal cells. The International Society for Cellular Therapy position statement. Cytotherapy, 8: 315-317. Dormady, S.P., Bashayan, O., Dougherty, R., Zhang, X.M., and Basch, R.S., (2001). Immortalized multipotential mesenchymal cells and the hematopoietic microenvironment. J. Hematother Stem Cell Res., 10: 125-140. Dovbeshko, G.I., Gridina, N.Y., Kruglova, E.B., and Pashchuk, O.P., (2000). FTIR spectroscopy studies of nucleic acid damage. Talanta, 53: 233-246. Dovbeshko, G.I., Chegel, V.I., Gridina, N.Y., Repnytska, O.P., Shirshov, Y.M., Tryndiak, V.P., Todor, I.M., and Solyanik, G.I., (2002). Surface enhanced IR absorption of nucleic acids from tumor cells: FTIR reflectance study. Biopolymer (Biospectroscopy), 67: 470-486. Downes, A., Mouras, R., and Elfick, A., (2010). Optical Spectroscopy for NoninvasiveMonitoring of Stem Cell Differentiation. Journal of Biomedicine and Biotechnology. J. Biomed. Biotechnol., 101864. Drummond-Barbosa, D., (2008). Stem cells, their niches and the systemic environment: an aging network. Genetics, 180: 1787-1797. Dukor, R., (2002). In Handbook of Vibrational Spectroscopy, Chalmers, J., Griffiths, P., Eds., Wiley: New York, 3335–3361.

135

Emerman, J.T., Bartley J.C., and Bissell, M.J., (1980). Interrelationship of glycogen metabolism and lactose synthesis in mammary epithelial cells of mice. Biochem. J., 192: 695-702. Emoto, K., and Umeda, M., (2001). Membrane lipid control of cytokinesis. Cell Struct. Funct. 26: 659-665. Erukhimovitch, V., Talyshinsky, M., Souprun, Y., Huleihel, M., (2005). FTIR microscopy detection of cells infected with viruses. Methods Mol. Biol., 292: 161-172. Fang, J., Menon, M., and Kapelle, W., (2007). EPO modulation of cell-cycle regulatory genes, and cell division, in primary bone marrow erythroblasts. Blood, 110: 2361-2370. Freifelder, D., (1982). Physical chemistry applications to biochemistry and

molecular biology. New York. Friedenstein, A.J., Piatetzky, S., and Petrakova, K.V., (1966). Osteogenesis

transplants of bone marrow cells. J. Embryol. Exp. Morphol., 16: 381-390. Fujioka, N., Morimoto, Y., Arai, T., and Kikuchi, M., (2004). Discrimination between normal and malignant human gastric tissues by Fourier transform infrared spectroscopy. Cancer Detection & Prevention, 28: 32-36 Gazi, E., Dwyer, J., Lockyer, N. P., Miyan, J., Gardner, P., Hart, C., Brown, M., and Clarke, N. W., (2005). Fixation protocols for subcellular imaging by synchrotron-based Fourier transform infrared microspectroscopy. Biopolymers, 77:18-30. Gaigneaux, A., Ruysschaert, J.M., and Goormaghtigh, E., (2006). Cell Discrimination by Attenuated Total Reflection–Fourier Transform Infrared Spectroscopy: The Impact of Preprocessing of Spectra. Appl. Spect., 60: 1022-1028.

Garip, S., Bozoğlu, F., and Severcan, F., (2007). Differentiation of Mesophilic and Thermophilic Bacteria with Fourier Transform Infrared Spectroscopy. Appl. Spectr., 61: 186-192.

Goldberg, M.E., and Chaffotte, A.F., (2005). Undistorted structural analysis of soluble proteins by attenuated total reflectance infrared spectroscopy. Protein Sci., 14: 2781-2792.

136

Gordon, M., (2010). Postgraduate Haematology. Wiley-Blackwell, 6th edition, Chapter 1, 1-12. Gorgulu, S.T., Doğan M., and Severcan, F., (2007). The Characterization and Differentiation of Higher Plants by Fourier Transform Infrared Spectroscopy. Appl. Spect., 61: 300-308. Gorgulu, S.T., (2009). Molecular investigation of PTZ-induced epileptic activites in rat brain cell membranes and the effects of vigabantin. PhD Thesis, Middle East Technical University. Greco, SJ., and Rameshwar, P., (2008). Microenvironmental considerations in the application of human mesenchymal stem cells in regenerative therapies. Biologics., 2: 699-705. Haris, P.I., and Severcan, F., (1999). FTIR spectroscopic characterization of protein structure in aqueous and non-aqueous media. J. Mol. Catal. B: Enzymatic, 7: 207-221. Hastings, G., Wang, R., Krug, P., Katz, D., and Hilliard, J., (2008). Infrared Microscopy for the Study of Biological Cell Monolayers. Spectral Effects of Acetone and Formalin Fixation. Biopolymers, 89: 921-930. Haynesworth, S.E., Baber, M.A., and Caplan, A.I., (1996). Cytokine expression by human marrow-derived mesenchymal progenitor cells in vitro: effects of dexamethasone and IL-1 alpha. J. Cell. Physiol., 166: 585-592. Horwitz, E.M., Le Blanc, K., Dominici, M., Mueller, I., Slaper-Cortenbach, I., Marini, F.C., Deans, R.J., Krause, D.S., Keating, A., (2005). Clarification of the nomenclature for MSC: The International Society for Cellular Therapy position Statement. Cytotherapy 7: 393-395.

Hsu S.C.P., (1997). Handbook of Instrumental Techniques for Analytical

Chemistry. Mallinckrodt, Inc. Mallinckrodt Baker Division, pp. 247-283.

Huang, K., Zhou, D.H., Huang, S.L., and Liang S.H., (2005). Age-related biological characteristics of human mesenchymal stem cells from different age donors. J. Exp. Hematol., 13: 1049-1053.

Ishii, K., Kimura, A., Kushibiki T., and Awazu K., (2007). Fourier transform infrared spectroscopic analysis of cell differentiation. Opt. in Tissue Eng. and Reg. Med. 6439.

137

Jackson, L., Jones, D.R., Scotting, P., and Sottile, V., (2007). Adult mesenchymal stem cells: differentiation potential and therapeutic applications. J. Postgrad. Med., 53: 121-127. Jackson. M., Ramjiawan, B., Hewko, M., and Mantsch, H.H., (1998). Infrared microscopic functional group mapping and spectral clustering analysis of hypercholesterolemic rabbit liver. Cell Mol. Biol., 44: 89-98. Jing, D., Fonseca, A.V., Alakel, N., Fierro, F.A., Muller, K., Bornhauser, M., Ehninger, G., Corbeil, D., and Ordemann, R., (2010). Hematopoietic stem cells in co-culture with mesenchymal stromal cells - modeling the niche compartments in vitro. Haematologica, 95: 542-550. Kaplan, R.N., Psaila B., and Lyden, D., (2006). Niche-to-niche migration of bone marrow-derived cells. Trends Mol. Med. 13: 72-81. Kasayama S, M Koga, H Kouhara. (1994). Unsaturated fatty acids are required for continuous proliferation of transformed androgen-dependent cells by fibroblast growth factor family proteins. Cancer Res 54:6441-6445. Kazarian, S.G., and Chan, K.L.A., (2006). Applications of ATR-FTIR spectroscopic imaging to biomedical samples. Biochimica et Biophysica Acta, 1758: 858-867. Kelly, E.B., (2007). Stem Cells, Green Wood Press, Wesport, Connecticut, London. Kemp, K.C, Hows, J, and Donaldson, C., (2005). Bone marrow-derived mesenchymal stem cells. Leuk Lymphoma. 46: 1531-44. Khandros, E., and Weiss, M.J., (2010). Protein quality control during erythropoiesis and hemoglobin synthesis. Hemat. Onco. Clinic. North Amer., 24: 1071-1088.

Khanmohammadi, M., Ansari, M.A., Garmarudi, A.B., Hassanzadeh, G., and Garoosi, G., (2007). Cancer diagnosis by discrimination between normal and malignant human blood samples using attenuated total reflectance-Fourier transform infrared spectroscopy. Cancer Invest., 25: 397-404. Kneipp, J., Lasch, P., Baldauf, E., Beekes, M., and Naumann, D., (2000). Detection of pathological molecular alterations in scrapie-infected hamster brain

138

by fourier transform infrared (FT-IR) spectroscopy. Biochim. Biophys. Acta, 1501: 189-199. Kneipp, J., Beekes, M., Lasch P., and Naumann, D., (2002). Molecular changes of preclinical scrapie can be detected by infrared spectroscopy. J. Neurosci., 22: 2989-2997. Krebsbach, P.H., Mankani, M.H., Satomura, K., Kuznetsov, S.A., and Robey, P.G., (1998). Repair of craniotomy defects using bone marrow stromal cells. Transplantation, 66: 1272-1278. Kretlow, A., Wang, Q., Kneipp, J., Lasch, P., Beekes, M., Miller, L., and Naumann, D., (2006). FTIR-microspectroscopy of prion-infected nervous tissue. Biochim. Biophys. Acta, 1758: 948-959. Kretlow, J.D., Jin, Y.Q., Liu, W., Zhang, W.J., Hong, T.H., Zhou, G., Baggett, L.S., Mikos, A.G., Cao, Y., (2008). Donor age and cell passage affects differentiation potential of murine bone marrow-derived stem cells. BMC Cell Biol., 9: 60. Kiel, M.J., and Morrison, S.J., (2006). Maintaining hematopoietic stem cells in the vascular niche. Immunity., 25: 977-988. Kirschstein, R., (2001). Stem Cells: Scientific Progress and Future Research

Directions. National Institutes of Health, Department of Health and Human Services. Kneipp, J., Lasch, P., Baldauf, E., Beekes, M., and Naumann, D., (2000). Detection of pathological molecular alterations in scrapie-infected hamster brain by Fourier transform infrared (FT-IR) spectroscopy. Biochim. Biophys. Acta, 1501: 189-199. Koc, O.N., Peters, C., Aubourg, P., Raghavan, S., Dyhouse, S., De Gasperi, R., Kolodny, E.H., Yoseph, Y.B., Gerson, S.L., Lazarus, H.M., Caplan, A.I., Watkins, P.A. and Krivit, W., (1999). Bone marrow-derived mesenchymal stem cells remain host-derived despite successful hematopoietic engraftment after allogeneic transplantation in patients with lysosomal and peroxisomal storage diseases. Exp. Hematol., 27: 1675-1681. Koch, T.G., Heerkens, T., Thomsen, P.D., Betts, D.H., (2007). Isolation of mesenchymal stem cells from equine umbilical cord blood. BMC Biotechnol., 30: 7:26.

139

Konorov, S.O., Schulze, H.G., Piret, J.M., Aparicio, S.A., Turner, R.F., and Blades, M.W., (2011). Raman microscopy-based cytochemical investigations of potential niche-forming inhomogeneities present in human embryonic stem cell colonies. Appl. Spectr., 65: 1009-1116. Krishnakumar, N., Manoharan, S., Palaniappan, P.L., Venkatachalam P., and Manohar, M.G., (2009). Chemopreventive efficacy of piperine in 7,12-dimethyl benzanthracene (DMBA)-induced hamster buccal pouch carcinogenesis: an FT-IR study. Food Chem. Toxicol., 47: 2813-2820. Krafft, C., Knetschke, T., Funk, R.H., and Salzer, R., (2006). Studies on stress-induced changes at the subcellular level by Raman microspectroscopic mapping. Anal. Chem., 78: 4424-4429. Krafft, C., Salzer, R., Seitz, S., Ern, C., and Schieker, M., (2007). Differentiation of individual human mesenchymal stem cells probed by FTIR microscopic imaging. Analyst, 132: 647–653. Lanzkowsky, P., (2000). Manual of Pediatric Hematology and Oncology. Third ed., San Diego, Academic Pres, 97-152. Lazarus, H.M., Koc, O.N., Devine, S.M., Curtin, P., Maziarz, R.T., Holland, H.K., Shpall, E.J., McCarthy, P., Atkinson, K., and Cooper, B.W., (2005). Cotransplantation of HLA-identical sibling culture-expanded mesenchymal stem cells and hematopoietic stem cells in hematologic malignancy patients. Biol. Blood Marrow Transplant., 11: 389-398. Lee, S.Y., Yoon, K.A., Jang, S.H., Ganbold, E.O., Uuriintuya, D., Shin, S.M., Ryu, P.D., and Joo, S.W., (2009). Infrared spectroscopy characterization of normal and lung cancer cells originated from epithelium. J. Vet. Sci., 10: 299-304.

Leitermann, F., Syldatk, C., and Hausmann, R., (2008). Fast quantitative determination of microbial rhamnolipids from cultivation broths by ATR-FTIR Spectroscopy. J. Biol. Eng., 7: 2-13.

Leskovjan, A.C., Kretlow, A., and Miller, L.M., (2010). Fourier transform infrared imaging showing reduced unsaturated lipid content in the hippocampus of a mouse model of Alzheimer's disease. Anal. Chem., 82: 2711-2716.

140

Lester, D.S., Kidder, L.H., Levin, I.W., and Lewis, E.N., (1998). Infrared microspectroscopic imaging of the cerebellum of normal and cytarabine treated rats. Cell Mol. Biol., 44: 29-38.

Libani, I.V., Guy, E.C., and Melchiori, L., (2008). Decreased differentiation of erythroid cells exacerbates ineffective erythropoiesis in β-thalassemia. Blood, 112: 875-885.

Li, L., Xie, T., (2005). Stem Cell Niche: Structure and Function, Annu. Rev. Cell Dev. Biol.. 21: 605-631.

Liquier, J., and Taillandier, E., (1996). Infrared spectroscopy of nucleic acids,

Infrared Spectroscopy of Biomolecules, Wiley-Liss, Inc., USA, 131-158.

Lithanatudom, P., Leecharoenkiat, A., Wannatung, T., Svasti, S., Fucharoen, S., and Smith, D.R., (2010). A mechanism of ineffective erythropoiesis in Beta-thalassemia/Hb E disease. Haematologica, 95: 716-723.

Liu, K., Jackson, M., Sowa, M.G., Ju, H., Dixon, I.M.C., and Mantsch, H.H., (1996). Modification of the extracellular matrix following myocardial infarction monitored by FTIR spectroscopy, Biochim. Biophys. Acta, 1315: 73–77. Liu, Z.J., Zhuge, Y., and Velazquez, O.C., (2009). Trafficking and differentiation of mesenchymal stem cells. J. Cell Biochem., 106: 984-991. Liu, K.Z., Bose, R., and Mantsch, H.H., (2002). Infrared spectroscopic study of diabetic platelets. Vibrational Spectroscopy, 28: 131-136. Loukopoulos, D., (1991). Thalassemia: Genotypes and phenotypes. Ann. Hematol., 62: 85-94. Lundbaek, J.A., Birn, P., Hansen, A.J., Sogaard, R., Nielsen, C., Girshman, J., Bruno, M.J., Tape, S.E., Egebjerg, J., Greathouse, D.V., Mattice, G.L., Koeppe R.E., and Andersen O.S., (2004). Regulation of sodium channel function by bilayer elasticity: the importance of hydrophobic coupling. Effects of micelle-forming amphiphiles and cholesterol. J. Gen. Physiol., 123: 599-621. Mader, S.S., Inquiry into Life, (1997). The McGraw-Hill Companies, Inc. Majumdar, M.K., Thiede, M.A., Mosca, J.D., Moorman, M., and Gerson, S.L., (1998). Phenotypic and functional comparison of cultures of marrow-derived mesenchymal stem cells (MSCs) and stromal cells. J. Cell Physiol., 176: 57-66.

141

Majumdar, M.K., Thiede, M.A,. Haynesworth, S.E., Bruder, S.P., and Gerson, S.L., (2000). Human marrow-derived mesenchymal stem cells (MSCs) express hematopoietic cytokines and support long-term hematopoiesis when differentiated toward stromal and osteogenic lineages. J. Hematother. Stem Cell Res., 9: 841-848. Mareschi, K., Ferrero, I., Rustichelli, D., Aschero, S., Gammaitoni, L., Aglietta, M., Madon, E., and Fagioli, F., (2006). Expansion of mesenchymal stem cells isolated from pediatric and adult donor bone marrow. J. Cell Biochem., 97: 744-754. Manoharan, R., Baraga, J.J., Rava, P.R., Dasari, R.R., Fitzmaurice, M., Feld, M.S., (1993). Biochemical analysis and mapping of atherosclerotic human artery using FT-IR microspectroscopy. Atherosclerosis 103: 181-193. Mantsch, H.H., (1984). Biological application of Fourier Transform Infrared Spectroscopy: A study of phase transitions in biomembranes. J. Mol. Struc., 113: 201-212. Matthaus, C., Boydston-White, S., Miljkovic, M., Romeo, M.J., and Diem, M., (2006). Raman and infrared microspectral imaging of mitotic cells. Appl Spectr., 60: 1–8. Melchiori, L., Gardenghi S., and Rivella, S., (2010). β-Thalassemia: HiJAKing ineffective erythropoiesis and iron overload. Adv. Hemat., Article ID 938640.

Melin, A., Perromat, A., and Deleris, G., (2000). Pharmacologic application of Fourier transform IR spectroscopy: In vivo toxicity of carbon tetrachloride on rat liver. Biopolymers (Biospectroscopy), 57: 160-168.

Mendelsohn, R., and Mantsch, H.H., (1986). Fourier transform infrared studies of lipid protein interaction. In: Progress in Protein-Lipid Interactions. 2: 103-147. Minguell, J.J., Erices, A., and Conget, P., (2001). Mesenchymal stem cells. Exp. Biol. Med., (Maywood) 226: 507-520. Mitsiadis, T.A., Barran, O., Rochat, A., Barrandon, Y., and De Bari, C., (2007). Stem cell niches in mammals. Exp. Cell Res., 313: 3377-3385. Moerman, E.J., Teng., K, and Lipschitz, D.A., (2004). Aging activates adipogenic and suppresses osteogenic programs in mesenchymal marrow stroma/stem cells:

142

the role of PPAR-γ2 transcription factor and TGF-β/BMP signaling pathways. Aging Cell, 3: 379-389. Mohsin, S., Shams, S., Khan, M., Javaid, A.S., Khan, S.N., and Riazuddin, S., (2011). Enhanced hepatic differentiation of mesenchymal stem cells after pretreatment with injured liver tissue. Differentiation, 81: 42-48 Moody, B., Haslauer, C.M., Kirk, E., Kannan, A., Loboa, E.G., and McCarty, G.S., (2010). In situ monitoring of adipogenesis with human-adipose-derived stem cells using surface-enhanced Raman spectroscopy. Appl Spectr. 64: 1227-1233. Moore, D.J., Sills, R.H., and Mendelsohn R., (1997). Conformational order of specific phospholipids in human erythrocytes: correlations with changes in cell shape. Biochemistry, 36: 660-664.

Olivieri, N.F., (1999). The β thalassemias. N. Engl. J. Med.341:99-109.

Ozek, N.S., Sara, Y., Onur, R., and Severcan, F., (2009). Low dose simvastatin induces compositional structural and dynamical changes in rat skeletal extensor digitorum longus muscle tissue. Biosci. Rep., 30: 41-50. Ozek, N.S., Tuna, S., Erson-Bensan, A.E., Severcan, F., (2010). Characterization of microRNA-125b expression in MCF7 breast cancer cells by ATR-FTIR spectroscopy. Analyst, 135: 3094-3102. Panno J., (2005). Stem Cell Research: Medical Applications and Ethical

Controversy. Parker F.S., (1971). Application of Infrared Spectroscopy in Biochemistry, Biology and Medicine. Plenum Press, New York. Peak D., (2004), Fourier transform tnfrared spectroscopy. Elsevier. Perkin Elmer Life and Analytical Sciences, (2005). FT-IR Spectroscopy-Attenuated Total Reflectance (ATR). Perkins A.C., (1998). Enrichment of blood from embryonic stem cells in vitro. Reprod. Fertil. Dev., 10: 563-572.

Peuchant, E., Richard-Harston, S., Bourdel-Marchasson, I., Dartigues, J.F., Letenneur, L., Barberger-Gateau P., Arnaud-Dabernat, S., and Danie, J.Y.,

143

(2008). Infrared spectroscopy: a reagent-free method to distinguish Alzheimer's disease patients from normal-aging subjects. Transl. Res., 152: 103-112. Pijanka, J.K., Kumar, D., Dale, T., Yousef, I., Parkes, G., Untereiner, V., Yang, Y., Dumas, P., Collins, D., Manfait, M., Sockalingum, G.D., Forsyth N.R., and Suso, J.S., (2010). Vibrational spectroscopy differentiates between multipotent and pluripotent stem cells, Analyst, 135: 3126-3132. Pittenger, M.F., Mackay, A.M., Beck, S.C., Jaiswal, R.K., Douglas, R., Mosca, J.D., Moorman M.A., Simonetti, D.W., Craig, S, and Marshak, D.R., (1999). Multilineage potential of adult human mesenchymal stem cells. Science 284: 143-147. Ponticiello, M.S., Schinagl, R.M., Kadiyala, S., and Barry, F.P., (2000). Gelatin-based resorbable sponge as a carrier matrix for human mesenchymal stem cells in cartilage regeneration therapy. J. Biomed.l Mat. Res., 52: 246–255. Purton L.E., and Scadden, D.T., (2011). The hematopoietic stem cell niche, Stem

Book, Harward Stem Cell Institute. Ramirez, J.M., Schaad, O., Durual, S., Cossali, D., Docquier, M., Beris, P., Descombes P., and Matthes, T., (2009). Growth differentiation factor 15 production is necessary for normal erythroid differentiation and is increased in refractory anaemia with ring-sideroblasts. Br J Haematol 144: 251-262. Rando, T.A., (2006). Stem cells, ageing and the quest for immortality. Nature, 441: 1080-1086. Richter, T., Steiner, G., Abu-Id, M.H., Salzer, R., Gergmann, R., Rodig, H., and Johannsen, B., (2002). Identification of tumor tissue by FTIR spectroscopy in com-bination with positron emission tomography. Vib. Spectr., 28: 103-110.

Rigas, B., Morgello, S., Goldman, I.S., and Wong, P.T.T., (1990). Human colorectal cancers display abnormal Fourier transform infrared spectra. Proc Natl Aca Sci USA, 87: 8140-8144. Rieger, K., Marinets, O., Fietz, T., Körper, S., Sommer, D., Mücke, C., Reufi, B., Blau, W.I., Thiel, E., and Knauf, W.U., (2005). Mesenchymal stem cells remain of host origin even a long time after allogeneic peripheral blood stem cell or bone marrow transplantation. Exp. Hematol. 33: 605-611.

144

Romeo, M.J., B. Mohlenhoff, and M. Diem, (2006). Infrared micro-spectroscopy of human cells: Causes for the spectral variance of oral mucosa (buccal) cells, Vib. Spectr., 42: 9-14. Romeo M.J., Boydston-White S., Matthaues C., Milkovic M., Bird B., Chernenko T., Lash P., nd Diem M., (2008). Infrared and Raman Microscopic Studies of

Individual Human Cells.

Roura S, Farré J, Soler-Botija C, Llach A, Hove-Madsen L, Cairó JJ, Gòdia F, Cinca J, Bayes-Genis A., (2006). Effect of aging on the pluripotential capacity of human CD105+ mesenchymal stem cells., Eur. J. Heart Fail., 8: 555-563. Orlic D., Bock, T.A., and Kanz, L., (1999). Hematopoietic stem cells biology and transplantation. Annals of The New York Academy of Sciences (New York, NY). Quarto, R., Mastrogiacomo, M., Cancedda, R., Kutepov, S.M., Mukhachev, V., Lavroukov, A., Kon, E., and Marcacci, M., (2001). Repair of large bone defects with the use of autologous bone marrow stromal cells. The New England Journal of Medicine, 344: 385–386. Sahu, R.K., Argov, S., Salman, A., Huleihel, M., Grossman, N., and Hammody, Z., (2004). Characteristic absorbance of nucleic acids in the Mid-IR region as possible common biomarkers for diagnosis of malignancy. Tech. Cancer Res. Treat., 3: 629-638. Sahu, R.K, Zelig U., Huleihel, M., Brosh, N., Talyshinsky, M., Ben-Harosh, M., Mordechai S., and Kapelushnik, J., (2006). Continuous monitoring of WBC (biochemistry) in an adult leukemia patient using advanced FTIR-spectroscopy. Leuk. Res., 30: 687-693.

Schrier, S.L., (2002). Pathophysiology of thalassemia. Curr. Opin. Hematol., 9: 123-126. Schultz, C.P., Liu, K.Z., Kerr, P.D., and Mantsch, H.H., (1998). In situ infrared histopathology of keratinization in human oral/oropharyngeal squamous cell carcinoma, Oncol. Res., 10: 277-286. Scutt, A., Kollenkirchen, U., and Bertram, P., (1996). Effect of age and overiectomy on fibroblastic colony-forming unit numbers in rat bone marrow. Calcif. Tissue Int., 59: 309-310.

145

Severcan, F., (1997). Vitamin E decreases the order of the phospholipid model membranes in the gel phase: An FTIR study. Biosci. Reports, 17: 231-235.

Severcan, F., and Haris, P.I., (1999). FTIR spectroscopic characterization of protein structure in aqueous and non-aqueous media. J. Mol. Cat. B. Enzy., 7: 207-221. Severcan, F., Toyran, N., Kaptan, N., and Turan, B., (2000). Foruier transform infrared study of the effect of diabetes on rat liver and heart tissues in the C-H region, Talanta, 53: 55-59. Severcan, F., Kaptan, N., and Turan, B., (2003). Fourier transform infrared spectroscopic studies of diabetic rat heart crude membranes, Spectroscopy, 17: 569–577. Severcan, M., Severcan, F., and Haris, I.P., (2004). Using artificially generated spectral data to improve protein secondary structure prediction from FTIR spectra of proteins, Anal. Biochem. 332: 238-244. Severcan, F., Gorgulu, G., Gorgulu, S.T., and Guray, T., (2005). Rapid monitoring of diabetes induced lipid peroxidation by Fourier transform infrared spectroscopy: Evidence from rat liver microsomal membranes, Anal. Biochem., 339: 36–40. Severcan F, O Bozkurt, R Gurbanov and G Gorgulu. (2010). FT-IR spectroscopy in diagnosis of diabetes in rat animal model. J Biophotonics 3: 621–631. Shamblott, M.J., Axelman, J., Wang, S., Bugg, E.M., Littlefield, J.W., Donovan, P.J., Blumenthal P.D., Huggins, G.R., Gearhart, J.D., Proc. Natl. Acad. Sci., 95: 13726-13731. Spector A.A., and Yorek, M.A., (1985). Membrane lipid composition and cellular function. J. Lipid Res., 26: 1015-1035. Steele, D., (1971). The Interpretation of Vibrational Spectra, William Clowes and Sons Lim., Great Britain. Steiner, G., Shaw, A., Choo-Smith, L.P., Abuid, M.H., Schackert, G., Sobottka, S., Steller, W., Salzer R., and Mantsch H.H., (2003). Distinguishing and grading human gliomas by IR spectroscopy. Biopolymers, 72: 464-471.

146

Stenderup, K., Justesen, J., Claudsen, C., (2003). Aging is associated with decreased maximal life span and accelerated senescence of bone marrow stromal cells. Bone, 33: 919-926. Stolzing, A., Scutt, A., (2006). Age-related impairment of mesenchymal progenitor cell function. Aging Cell, 5: 213-224. Stuart, B., (1997). Biological Applications of Infrared Spectroscopy. John Wiley and Sons, Ltd., England. Szczerbowska-Boruchowska, M., Dumas, P., Kastyak, M.Z., Chwiej, J., Lankosz, M., Adamek, D., Krygowska-Wajs, A., (2007). Biomolecular investigation of human substantia nigra in Parkinson's disease by synchrotron radiation Fourier transform infrared microspectroscopy, Archives of Biochemistry and Biophysics, 459: 241-248.

Tabbara, I. A., Zimmerman, K., Morgan, C., and Nahleh, Z., (2002). Allogeneic hematopoietic stem cell transplantation: complications and results. Archives of Internal Medicine, 162: 1558-1566. Taillandier, E., and Liquier, J., (1999). Infrared spectroscopy of DNA. Methods Enzymol., 211: 307-335. Takahashi, H., French, S.M., and Wong, P.T.T., (1991). Alterations in hepatic lipids and proteins by Chronic ethanol Intake: A highpressure fourier transform Infrared spectroscopic study on alcoholic liver disease in the rat alcohol. Clin. Exp. Res., 15: 219-223. Tanno, T., Noel, P., and Miller, J.L., (2010). Growth differentiation factor 15 in erythroid health and disease. Curr Opin Hematol 17: 184-90. Tanthanuch, W., Thumanu, K., Lorthongpanich, C., Parnphi R., and Heraud P., (2010). Neural differentiation of mouse embryonic stem cells studied by FTIR spectroscopy. J. Mol. Structr., 967: 189-195. Thalmeier., K, Meissner., P, Reisbach, G, Hültner, L., Mortensen, B.T., Brechtel, A., Oostendorp, R.A., and Dörmer, P., (1996). Constitutive and modulated cytokine expression in two permanent human bone marrow stromal cell lines. Exp. Hematol., 24: 1-10. Thumanu, K., Tanthanuch, W., Ye, D., Sangmalee, A., Lorthongpanich, C., Parnpai, R., and Heraud, P., (2011). Spectroscopic signature of mouse embryonic

147

stem cell-derived hepatocytes using synchrotron Fourier transform infrared microspectroscopy, J.Biomed.Opt., 16: 057005.

Timlin, J.A., Laura, E.M., Lyons, C.R., Hjelle, B., and Alam, M.K., (2009). Dynamics of cellular activation as revealed by attenuated total reflectance infrared spectroscopy. Vibr. Spect., 50: 78–85.

Titushkin, I., and Cho, M., (2006). Distinct membrane mechanical properties of human mesenchymal stem cells determined using laser optical tweezers. Biophys. J., 90: 2582–2591.

Tokalov, S.V., Grüner, S., and Schindler, S., (2007). Age-related changes in the frequency of mesenchymal stem cells in the bone marrow of rats. Stem Cells Dev., 16: 439-446.

Toyran, N., and Severcan, F., (2003). Competitive effect of vitamin D2 and Ca2+

on phospholipids model membranes: An FTIR study, Chem. Phys. Lipids, 123: 165-176.

Toyran, N., Zorlu, F., Donmez, G., Oge, K., Severcan, F., (2004). Chronic hypoperfusion alters the content and structure of proteins and lipids of rat brain homogenates: a Fourier Transform Infrared Spectroscopic study, Eur. Biophy. J. , 33: 549-554. Trombetta, D., Gangemi, S., Saija A., Minciullo, P.L., Cimino, F., Cristani, M., Briuglia, S., Piraino, B., Isola, S., and Salpietro, C.D., (2006). Increased protein carbonyl groups in the serum of patients affected by thalassemia major. Ann. Hematol. 85: 520–522. Tsavachidou, D., Li, Y., Guo, H., Liu, W., Jonasch, E., Tamboli, P., and Mills, G.B., (2010). Glycogen metabolism provides nutritional support to renal cancer cells under conditions of stress and may serve as a marker of response to antiangiogenic therapy with bevacizumab. Fourth AACR International Conference on Molecular Diagnostics in Cancer Therapeutic. Denver, CO. Oral Prensentation. Umemura, J., Cameron, G., and Mantsch, H.H., (2000). A Fourier transform infrared spectroscopic study of the molecular interaction of cholesterol with 1,2-dipalmitoyl-sn-glycero-3-phosphocholine. Biochim. Biophys. Acta, 602: 32-44.

Vacek, A., (2000). Proliferation activity and number of stromal (CFU-f) and haemopoietic (CFUs) stem cells in bone marrow and spleen of rats of different ages. Acta Vet., 69: 25-31.

148

Van de Loosdrecht, A.A., Beelen, R.H., Ossenkoppele, G.J., Broekhoven, M.G., Langenhuijsen, M.M., (1994). A tetrazolium-based colorimetric MTT assay to quantitate human monocyte mediated cytotoxicity against leukemic cells from cell lines and patients with acute myeloid leukemia. J. Immunol. Methods, 174: 311-320.

Villaron, E.M., Almeida, J., López-Holgado, N., Alcoceba, M., Sánchez-Abarca, L.I., Sanchez-Guijo, F.M., Alberca, M., Pérez-Simon, J.A., San Miguel, J.F., Del Cañizo M.C., (2004). Mesenchymal stem cells are present in peripheral blood and can engraft after allogeneic hematopoietic stem cell transplantation. Haematologica, 89:1421-1427.

Wagner, W., Roderburg, C., Wein, F., Diehlmann, A., Frankhauser, M., Schubert, R., (2007). Molecular and secretory profiles of human mesenchymal stromal cells and their abilities to maintain primitive hematopoietic progenitors. Stem Cells, 25: 2638-2647.

Wagner, W., Horn, P., Bork, S., Ho, A.D., (2008). Aging of hematopoietic stem cells is regulated by the stem cell niche. Exp. Gerontol., 43: 974-980.

Wagner, W., Bork, S., Lepperdinger, G., Joussen, S., Ma, N., Strunk, D., Koch, C., (2010). How to track cellular aging of mesenchymal stromal cells? Aging (Albany NY), 2: 224-230.

Walkley, C.R., (2011). Erythropoiesis, anemia and the bone marrow microenvironment. Int. J. Hematol., 93:10-13.

Wang, J., Chi, C., Lin, S., and Chern, Y., (1997). Conformational changes in gastric carcinoma cell membrane protein correlated to cell viability after treatment with adamantyl maleimide, Anticancer Research, 17: 3473-3478.

Whitman, M., (1998). Smads and early developmental signaling by the TGF beta superfamily. Genes Dev., 12: 2445-2462.

Wilson, A., Shehadeh, L.A., Yu, H., Webster, K.A., (2010). Age-related molecular genetic changes of murine bone marrow mesenchymal stem cells. BMC Genomics, 7: 11:229.

Winder, C.L., Goodacre, R., (2004). Comparison of diffuse-reflectance absorbance and attenuated total reflectance FT-IR for the discrimination of bacteria. Analyst, 129: 1118-11122.

149

Wong, P.T.T., Wong, R.K., Caputo, T.A., Godwin, T.A., Rigas, B., (1991). Infrared spectroscopy of exfoliated human cervical cells: Evidence of extensive structural changes during carcinogenesis. Proc. Nati. Acad. Sci., 88: 10988-10992.

Wood, B.R., Tait, B., and McNaughton, D., (2000). Fourier transform infrared spectroscopy as a tool for detecting early lymphocyte activation: A new approach to histocompatibility matching. Human Immuno, 61: 1307–1315.

Yan, X., Anlin, L., Xing, Y., Wang, L., Zhao, W., (2010). Recent progress in the differentiation of bone marrow derived mesenchymal stem cells (BMMSCs) to cardiomyocyte- like cells and their clinical application. African J. of Biotech., 9: 5042-5047.

Yang, Y., Sule-Suso, J., Sockalingum, G.D., Kegelaer, G., Manfait, M., and El Haj, A.J., (2005) Study of tumor cell invasion by Fourier transform infrared micro-spectroscopy. Biopolymers, 78: 311-317.

Yano, K., Ohoshima, S., Shimmizu, Y., Moriguchi, T., Katayama, H., (1996). Evaluation of glycogen level in human lung carcinoma tissues by an infrared spectroscopic method, Cancer Lett., 110: 29-34.

Young, R.G., Butler, D.L., Weber, W., Caplan, A.I., Gordon, S.L., and Fink, D.J., (1998). Use of mesenchymal stem cells in a collagen matrix for Achilles tendon repair. J. Orth. Res., 16: 404-413.

Yu, J., He, H., Tang, C., Zhang, G., Li, Y., Wang, R., Shi, J., and Jin, Y. (2010). Differentiation potential of STRO-1+ dental pulp stem cells changes during cell passaging. BMC Cell Biol., 8: 11- 32. Zeng, R., Wang, L.W., Hu Z.B., Guo, W.T., Wei J.S., Lin H., Sun, X., Chen, L.X., Yang L.J., (2011). Differentiation of Human Bone Marrow Mesenchymal Stem Cells into Neuron-like Cells in-vitro. Spine (Phila Pa 1976), 36: 997-1005. Zheng , H., Martin, J.A., and Duwayri, Y., (2007). Impact of aging on rat bone marrow-derived stem cell chondrogenesis. J. Gerontol. A Biol. Sci. Med. Sci., 62: 136-148.

Zhukareva, V., Obrocka, M., Houle, J.D., Fischer, I., and Neuhuber, B., (2010). Secretion profile of human bone marrow stromal cells: Donor variability and response to inflammatory stimuli. Cytokine, 50: 317-321.

150

APPENDIX A

CHEMICALS

AlizerinRed Stain Sigma

Ascorbic acid Sigma

Beta glycerophosphate Sigma

Dexamethasone Sigma

DiMethylSulfoxide Applichem

Dulbeco’s Modified Eagle Medium-Low Glucose BiochromAG

EPO R&D Systems

Fetal Bovine Serum Biochrom AG

Ficoll Biochrom AG

Formol Sigma

GDF 15 R&D Systems

IBMX Sigma

Igepal/isopropanol Sigma

Indomethacine Sigma

Insulin Sigma

L-glutamine Biochrom AG

Oil Red O Sigma

Penicillin/Streptomycin Biochrom AG

Phosphate Buffer Saline Sigma

Quantichrom Calcium Assay Kit Bioassay Systems

Thiazolyl Blue Tetrazolium Bromide Sigma

151

CURRICULUM VITAE

PERSONEL INFORMATION

Surname, Name: Aksoy, Ceren Nationality: Turkish (TC) Date and Place of Birth: 05 November 1979, Ankara Marital Status: Single Phone: +90 312 210 51 57 E-mail: cerenaksoyyy@yahoo.com Foreign Languages: English EDUCATION Degree Institution Graduation C.GPA Ph.D. METU Biology Dept. 2012 3.21/4 M.Sc. METU Biology Dept. 2004 3.1/4 B.Sc. Ankara Univ. Biology Dept. 2000 89/100 WORK EXPERIENCE Year Place Enrollment 2004-2011 Technopark-METU Project Developer&Manager AWARDS and SCHOLARSHIPS The Best Scientific Poster Award “1st International Conference on Stem Cell Research and Applications” to be held between October 7-9, 2011 in Kayseri, Turkey”. Scholarship from Turkish Scientific and Research Council of Turkey during my MSc.

152

PUBLICATIONS A) Book Chapters “Characterization of Stem Cells by Vibrational Spectroscopy” in Application of Vibrational Spectroscopy in Diagnosis and Screening” by Feride Severcan and Parvez I. Haris, IOS Press in 2012. B) Articles in refereed Journals (SCI)

1. Aksoy C., Guliyev A., Kilic E., Uckan D., Severcan F.; “Bone Marrow Mesenchymal Stem Cells in Patients with Beta Thalassemia Major: Molecular Analyses with Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) Spectroscopy Study As A Novel Method”. In press, Stem Cells and Development, DOI number: 10.1089/scd.2011.0444.

2. Aksoy C., Severcan F. “Role of Vibrational Spectroscopy in Stem Cell

Research”. Invited Review Article, submitted for publication. Paper has been accepted for publication by Spectroscopy–Biomedical Applications.

3. Gurakan G. C., Aksoy C., Ogel Z. B., Oren N. G.; “Differentiation of

Salmonella Typhimurium from Salmonella Enteritidis and other Salmonella serotypes using Random Amplified Polymorphic DNA Analysis”. Poultry Science, 2008; 87: 1068-1074.

C) Articles in preperation:

1. Aksoy C., Uckan D., Severcan F. “Characterization of Donor Age Effect in Mesenchymal Stem Cell by ATR-FTIR spectroscopy. (Research Article)

2. Aksoy C., Uckan D., Severcan F. “FTIR microspecroscopy as a novel

method in characterization of Mesenchymal Stem Cells at healthy and disease states. (Research Article)

D) Poster Presentations in International Meetings: Aksoy C., Uckan D., Severcan F.; “Investigation of Bone Marrow Mesenchymal Stem Cell Properties in Patients with Beta Thalassemia Major: FTIR Spectroscopy and Imaging Study.” "FT-IR Spectroscopy in Microbiological and Medical Diagnostics", Robert Koch-Institute, October 20-21, 2011 in Berlin, Germany. Aksoy C., Guliyev A., Kilic E., Uckan D., Severcan F.; “Investigation of Bone Marrow Mesenchymal Stem Cell Properties in Patients with Beta Thalassemia

153

Major: Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) Spectroscopy Study”. Presented at; “1st Annual Congress on Stem Cell Research”, September 28-October 2 in Kocaeli, Turkey. and “1st International Conference on Stem Cell Research and Applications” October 7-9, 2011 in Kayseri, Turkey” (Best Scientific Poster Award). Aksoy C., Uckan D., Severcan F.; “Investigation of Donor Age Effect on Healthy Human Bone Marrow Mesenchymal Stem Cells”. “1st International Conference on Stem Cell Research and Applications” October 7-9, 2011 in Kayseri, Turkey. E) Poster Presentations in National Meetings: Aksoy C., Guliyev A., Kilic E., Uckan D., Severcan F.; “Beta Talasemi Major Hastalığında Kemik İliği Mezenkimal Kök Hücrelerinin ATR-FTIR (Attenuated Total Reflectance- Fourier Dönüşüm Kızıl Ötesi) Spektroskopisi Yöntemi ile Moleküler Seviyede İncelenmesi. 23. Ulusal Biyofizik Kongresi, 13-16 Eylül 2011, Edirne, Türkiye. Aksoy C., Severcan F., Uckan D. “Investigation of Donor Age Effect on Healthy Human Bone Marrow Mesenchymal Stem Cells”. ODTÜ Biyolojik Bilimler Bölümü Araştırma Günü, 2011, ODTÜ-Ankara, Türkiye. Aksoy C., Severcan F., Uckan D.; “Biomedical Applications of FTIR Spectroscopy on Human Mesenchymal Stem Cells”, The 5th Nanoscience and Nanotechnology Conference (NanoTR5) , June 08-12 2009, Eskişehir, Turkiye. Aksoy C., Severcan F., Çetinkaya Uçkan D., “Insan Mezenkimal Kök Hücrelerinde Donor Yaşının Etkilerinin Moleküler Düzeyde FTIR-Spektroskopisi Yöntemi ile Saptanması”, 20. Ulusal Biyofizik Kongresi, 2008, Mersin, Türkiye. Aksoy C., Ögel Z.B., Gürakan G.C., “Salmonella typhimurium için Serotip Spesifik DNA İşaretleyicisinin RAPD-PCR Metodu ile Tanısı”. "XIV. Biyoteknoloji Kongresi, 2005 Eskişehir, Türkiye.

154

PROJECTS

• “Investigation of Donor Age Effect on Healthy Human Bone Marrow Mesenchymal Stem Cells at Molecular Level by FTIR Spectroscopy” (ODTU-BAP Project Funds).

• Project Preparation and Management:: “Interactive Educational Material

for Pediatric Bone Marrow Transplantation Nurses” (EC-Leonardo da Vinci Project Programme, 503223-LLP-1-2009-1-TR-Leonardo-LMP).

• Project Preparation and Management: “A Guardian Angel for Extended Home Environment” (2008 ITEA2 Project Programme, ITEA2 08018).

• Project Preparation: “Improvement of the Scientific and Technological Research Capacity of “Pediatric Stem Cell Research, Development, Cellular therapy and Continuous Training Centre (PEDI-STEM)”” (FP7-REGPOT-2008-1 Project Programme)

• Project Preparation and Management: “E-Training of Medical Staff to

Reach Adolescents of Different Cultures” (EC-Leonardo da Vinci Project Programme, 2006-TR/06/B/F/PP/178010).

• Project Preparation: “Early Identification of Alzhemier Disease by Multi-

Mode Optical Imaging Systems”2534 programme code, 2+2 Turkey-Germany International Cooperation Project Programme. Project was accepted in first evaluation step.